diff --git a/CHANGELOG.rst b/CHANGELOG.rst
index 9a7c8f806..00d4dc9e6 100644
--- a/CHANGELOG.rst
+++ b/CHANGELOG.rst
@@ -1,8 +1,13 @@
 Change Log
 =============
-[0.5.0] - 2020-01-xx
+
+[0.5.0] - 2020-01-23
 --------------------
-- [FIXED] A bug in the conversion from pair unit to kv in pandapower backend. Adding some tests for that too.
+- [BREAKING] Action/Backend has been modified with the implementation of redispatching. If
+  you used a custom backend, you'll have to implement the "redispatching" part.
+- [BREAKING] with the introduction of redispatching, old action space and observation space,
+  stored as json for example, will not be usable: action size and observation size
+  have been modified.
 - [ADDED] A converter class that allows to pre-process observation, and post-process action
   when given to an `Agent`. This allows for more flexibility in the `action_space` and
   `observation_space`.
@@ -11,27 +16,21 @@ Change Log
 - [ADDED] Redispatching possibility for the environment
 - [ADDED] More complete documentation of the representation of the powergrid
   (see documentation of `Space`)
+- [FIXED] A bug in the conversion from pair unit to kv in pandapower backend. Adding some tests for that too.
 - [UPDATED] More complete documentation of the Action class (with some examples)
 - [UPDATED] More unit test for observations
-- [UPDATED] Remove the TODO's already coded (no more todo then)
+- [UPDATED] Remove the TODO's already coded
 - [UPDATED] GridStateFromFile can now read the starting date and the time interval of the chronics.
-- [BREAKING] Action/Backend has been modified with the implementation of redispatching. If
-  you used a custom backend, you'll have to implement the "redispatching" part.
-- [BREAKING] with the introduction of redispatching, old action space and observation space,
-  stored as json for example, will not be usable: action size and observation size
-  have been modified.
+- [UPDATED] Documentation of Observation: adding the units
+  (`issue 22 <https://github.com/rte-france/Grid2Op/issues/22>`_)
+- [UPDATED] Notebook `getting_started/4_StudyYourAgent.ipynb` to use the converter now (much shorter and clearer)
+
+[0.4.3] - 2020-01-20
+--------------------
+- [FIXED] Bug in L2RPN2019 settings, that had not been modified after the changes of version 0.4.2.
 
 [0.4.2] - 2020-01-08
 --------------------
-- [FIXED] Runner cannot save properly action and observation (sizes are not computed properly)
-  **now fixed and unit test added**
-- [FIXED] Plot utility has a bug in extracting grid information.
-  **now fixed**
-- [FIXED] gym compatibility issue for environment
-- [FIXED] checking key-word arguments in "make" function: if an invalid argument is provided,
-  it now raises an error.
-- [UPDATED] multiple random generator streams for observations
-- [UPDATED] Refactoring of the Action and Observation Space. They now both inherit from "Space"
 - [BREAKING] previous saved Action Spaces and Observation Spaces (as dictionnary) are no more compatible
 - [BREAKING] renaming of attributes describing the powergrid across classes for better consistency:
 
@@ -62,7 +61,16 @@ Action / Observation  _lines_ex_pos_topo_vect  lines_ex_pos_topo_vect
 GridValue             n_lines                  n_line
 ====================  =======================  =======================
 
-- [UPDATE] the getting_started notebooks to reflect these changes
+- [FIXED] Runner cannot save properly action and observation (sizes are not computed properly)
+  **now fixed and unit test added**
+- [FIXED] Plot utility has a bug in extracting grid information.
+  **now fixed**
+- [FIXED] gym compatibility issue for environment
+- [FIXED] checking key-word arguments in "make" function: if an invalid argument is provided,
+  it now raises an error.
+- [UPDATED] multiple random generator streams for observations
+- [UPDATED] Refactoring of the Action and Observation Space. They now both inherit from "Space"
+- [UPDATED] the getting_started notebooks to reflect these changes
 
 [0.4.1] - 2019-12-17
 --------------------
@@ -72,25 +80,25 @@ GridValue             n_lines                  n_line
 [0.4.0] - 2019-12-04
 --------------------
 - [ADDED] Basic tools for plotting with the `PlotPlotly` module
-- [UPDATED] handling of the `AmbiguousAction` and `IllegalAction` exceptions (and appropriated tests)
 - [ADDED] support of maintenance operation as well as hazards in the Observation (and appropriated tests)
 - [ADDED] support for maintenance operation in the Environment (read from the chronics)
+- [ADDED] example of chronics with hazards and maintenance
+- [UPDATED] handling of the `AmbiguousAction` and `IllegalAction` exceptions (and appropriated tests)
 - [UPDATED] various documentation, in particular the class Observation
 - [UPDATED] information retrievable `Observation.state_of`
-- [ADDED] example of chronics with hazards and maintenance
 
 [0.3.6] - 2019-12-01
 --------------------
-- [UPDATED] Readme with docker
 - [ADDED] functionality to restrict action based on previous actions
   (impacts `Environment`, `GameRules` and `Parameters`)
 - [ADDED] tests for the notebooks in `getting_started`
 - [UPDATED] readme to properly show the docker capability
+- [UPDATED] Readme with docker
 
 [0.3.5] - 2019-11-28
 --------------------
 - [ADDED] serialization of the environment modifications
-- [FIXED] error messages in `grid2op.GridValue.check_validity`
 - [ADDED] the changelog file
-- [UPDATED] notebook getting_started/4_StudyYourAgent.ipynb to reflect these changes
-- [ADDED] serialization of hazards and maintenance in actions (if any)
\ No newline at end of file
+- [ADDED] serialization of hazards and maintenance in actions (if any)
+- [FIXED] error messages in `grid2op.GridValue.check_validity`
+- [UPDATED] notebook `getting_started/4_StudyYourAgent.ipynb` to reflect these changes
diff --git a/docs/conf.py b/docs/conf.py
index 3eb682d47..9f54e7a6a 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -22,8 +22,8 @@
 author = 'Benjamin Donnot'
 
 # The full version, including alpha/beta/rc tags
-release = '0.4.3'
-version = '0.4'
+release = '0.5.0'
+version = '0.5'
 
 
 # -- General configuration ---------------------------------------------------
diff --git a/docs/index.rst b/docs/index.rst
index a5ac45cec..58344f8a5 100644
--- a/docs/index.rst
+++ b/docs/index.rst
@@ -53,6 +53,7 @@ Technical Documentation
    :maxdepth: 1
 
    action
+   converters
    agent
    backend
    backendpp
diff --git a/getting_started/0_basic_functionalities.ipynb b/getting_started/0_basic_functionalities.ipynb
index e3a024736..f6bdde483 100644
--- a/getting_started/0_basic_functionalities.ipynb
+++ b/getting_started/0_basic_functionalities.ipynb
@@ -47,7 +47,16 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "pygame 1.9.6\n",
+      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
+     ]
+    }
+   ],
    "source": [
     "import os\n",
     "import sys\n",
@@ -520,7 +529,7 @@
      "output_type": "stream",
      "text": [
       "This agent managed to survive 11 timesteps\n",
-      "It's final cumulated reward is 11.0\n"
+      "It's final cumulated reward is 219.99783718276583\n"
      ]
     }
    ],
@@ -613,7 +622,7 @@
      "output_type": "stream",
      "text": [
       "The results are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
       "\t\t - cumulative reward: 10.00\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
@@ -645,7 +654,7 @@
      "output_type": "stream",
      "text": [
       "The results are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
       "\t\t - cumulative reward: 10.00\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
@@ -687,7 +696,7 @@
      "output_type": "stream",
      "text": [
       "The results are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
       "\t\t - cumulative reward: 10.00\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
diff --git a/getting_started/1_Observation_Agents.ipynb b/getting_started/1_Observation_Agents.ipynb
index f884f2f89..ff3377955 100644
--- a/getting_started/1_Observation_Agents.ipynb
+++ b/getting_started/1_Observation_Agents.ipynb
@@ -54,7 +54,16 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "pygame 1.9.6\n",
+      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
+     ]
+    }
+   ],
    "source": [
     "import os\n",
     "import sys\n",
@@ -389,9 +398,9 @@
      "text": [
       "Loads active consumption: [18.8 85.1 13.8 44.3  7.1 10.2 27.1  8.2  3.2  5.7 11.8]\n",
       "Loads reactive consumption: [47.13340788 58.60853089 14.68417071 23.59794742 -0.49975794]\n",
-      "Loads voltage (voltage magnitude of the bus to which it is connected) : [141.075        0.21788455   0.21533202   0.21830444   0.21692824\n",
-      "   0.2111932  137.68220138   0.22256     14.72610185  13.08\n",
-      "   0.21591106]\n"
+      "Loads voltage (voltage magnitude of the bus to which it is connected) : [141.075      136.35         0.2111932  136.42874991 137.68220138\n",
+      "   0.22256      0.21591106   0.21533202   0.21788455   0.21830444\n",
+      "   0.21692824]\n"
      ]
     }
    ],
@@ -577,9 +586,9 @@
        "        1.31000000e+01,  6.01000000e+01,  9.50000000e+00,  3.15000000e+01,\n",
        "        4.90000000e+00,  7.10000000e+00,  1.91000000e+01,  5.80000000e+00,\n",
        "        2.20000000e+00,  4.00000000e+00,  8.40000000e+00,  1.41075000e+02,\n",
-       "        2.17884546e-01,  2.15332022e-01,  2.18304445e-01,  2.16928244e-01,\n",
-       "        2.11193196e-01,  1.37682201e+02,  2.22560000e-01,  1.47261019e+01,\n",
-       "        1.30800000e+01,  2.15911056e-01,  1.08718903e+02,  4.07658248e+01,\n",
+       "        1.36350000e+02,  2.11193196e-01,  1.36428750e+02,  1.37682201e+02,\n",
+       "        2.22560000e-01,  2.15911056e-01,  2.15332022e-01,  2.17884546e-01,\n",
+       "        2.18304445e-01,  2.16928244e-01,  1.08718903e+02,  4.07658248e+01,\n",
        "       -8.32701461e+00,  4.06838088e-01, -1.65603459e+01,  3.00462070e+00,\n",
        "        1.37826937e+01,  4.38146976e+01,  2.86127910e+01,  1.54475549e+01,\n",
        "       -1.88518005e+01, -5.44944509e+01,  2.03193013e+01,  8.80848061e+00,\n",
@@ -1079,7 +1088,7 @@
      "output_type": "stream",
      "text": [
       "The results for DoNothing agent are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
       "\t\t - cumulative reward: 199.998003\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
@@ -1119,7 +1128,7 @@
      "output_type": "stream",
      "text": [
       "The results for the custom agent are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
       "\t\t - cumulative reward: 199.998003\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
@@ -1163,8 +1172,8 @@
      "output_type": "stream",
      "text": [
       "The results for the PowerLineSwitch agent are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
-      "\t\t - cumulative reward: 199.998134\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
+      "\t\t - cumulative reward: 199.998150\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
     }
diff --git a/getting_started/2_Action_GridManipulation.ipynb b/getting_started/2_Action_GridManipulation.ipynb
index 5d13585f1..ba25f04e3 100644
--- a/getting_started/2_Action_GridManipulation.ipynb
+++ b/getting_started/2_Action_GridManipulation.ipynb
@@ -54,7 +54,16 @@
    "cell_type": "code",
    "execution_count": 1,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "pygame 1.9.6\n",
+      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
+     ]
+    }
+   ],
    "source": [
     "import os\n",
     "import sys\n",
@@ -460,6 +469,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - force reconnection of 2 powerlines ([3 4])\n",
       "\t - force disconnection of 2 powerlines ([5 6])\n",
       "\t - switch status of 3 powerlines ([0 1 2])\n",
@@ -504,6 +514,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - force reconnection of 2 powerlines ([3 4])\n",
       "\t - force disconnection of 2 powerlines ([5 6])\n",
       "\t - switch status of 3 powerlines ([0 1 2])\n",
@@ -579,6 +590,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - NOT force any line status\n",
       "\t - NOT switch any line status\n",
       "\t - NOT switch anything in the topology\n",
@@ -617,6 +629,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - NOT force any line status\n",
       "\t - NOT switch any line status\n",
       "\t - Change the bus of the following element:\n",
@@ -648,6 +661,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - NOT force any line status\n",
       "\t - NOT switch any line status\n",
       "\t - NOT switch anything in the topology\n",
@@ -681,6 +695,7 @@
      "text": [
       "This action will:\n",
       "\t - NOT change anything to the injections\n",
+      "\t - NOT perform any redispatching action\n",
       "\t - NOT force any line status\n",
       "\t - NOT switch any line status\n",
       "\t - NOT switch anything in the topology\n",
@@ -710,22 +725,19 @@
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "This action will:\n",
-      "\t - NOT change anything to the injections\n",
-      "\t - force reconnection of 1 powerlines ([1])\n",
-      "\t - NOT switch any line status\n",
-      "\t - NOT switch anything in the topology\n",
-      "\t - Set the bus of the following element:\n",
-      "\t \t - assign bus 1 to line (origin) 1 [on substation 0]\n",
-      "\t \t - assign bus 1 to line (extremity) 1 [on substation 4]\n"
+     "ename": "TypeError",
+     "evalue": "reconnect_powerline() got an unexpected keyword argument 'l_id'",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-13-c91305fbc1f4>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mreconnecting_line_1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0maction_space\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mreconnect_powerline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ml_id\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbus_or\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mbus_ex\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      2\u001b[0m \u001b[0mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mreconnecting_line_1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
+      "\u001b[0;31mTypeError\u001b[0m: reconnect_powerline() got an unexpected keyword argument 'l_id'"
      ]
     }
    ],
    "source": [
-    "reconnecting_line_1 = action_space.reconnect_powerline(l_id=1,bus_or=1,bus_ex=1)\n",
+    "reconnecting_line_1 = action_space.reconnect_powerline(line_id=1,bus_or=1,bus_ex=1)\n",
     "print(reconnecting_line_1)"
    ]
   },
@@ -751,23 +763,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "This action will:\n",
-      "\t - NOT change anything to the injections\n",
-      "\t - NOT force any line status\n",
-      "\t - NOT switch any line status\n",
-      "\t - NOT switch anything in the topology\n",
-      "\t - Set the bus of the following element:\n",
-      "\t \t - assign bus 2 to generator 0 [on substation 1]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "my_act = action_space.set_bus(\"gen_1_0\", # mandatory name of the element\n",
     "                                 new_bus=2, # mandatory the new bus to connect it too\n",
@@ -779,24 +777,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "This action will:\n",
-      "\t - NOT change anything to the injections\n",
-      "\t - NOT force any line status\n",
-      "\t - NOT switch any line status\n",
-      "\t - NOT switch anything in the topology\n",
-      "\t - Set the bus of the following element:\n",
-      "\t \t - assign bus 2 to line (origin) 8 [on substation 1]\n",
-      "\t \t - assign bus 2 to generator 0 [on substation 1]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "action_space.set_bus(\"1_3_8\", # mandatory name of the element\n",
     "                              extremity=\"or\", # mandatory, which extrmity to change\n",
diff --git a/getting_started/3_TrainingAnAgent.ipynb b/getting_started/3_TrainingAnAgent.ipynb
index 1a1ac6f68..b4a6e72ea 100644
--- a/getting_started/3_TrainingAnAgent.ipynb
+++ b/getting_started/3_TrainingAnAgent.ipynb
@@ -245,7 +245,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 3,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -273,7 +273,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [
     {
@@ -300,7 +300,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -397,7 +397,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -438,7 +438,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -513,7 +513,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -569,7 +569,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -632,7 +632,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 39,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -834,7 +834,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 34,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -908,7 +908,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 35,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1081,7 +1081,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 36,
+   "execution_count": 13,
    "metadata": {},
    "outputs": [
     {
@@ -1092,41 +1092,51 @@
       "Instructions for updating:\n",
       "Colocations handled automatically by placer.\n",
       "Successfully constructed networks.\n",
-      "Lived with maximum time  50\n",
-      "Earned a total of reward equal to  999.9920304611152\n",
       "WARNING:tensorflow:From /home/donnotben/.local/lib/python3.6/site-packages/tensorflow/python/ops/math_ops.py:3066: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
       "Instructions for updating:\n",
       "Use tf.cast instead.\n",
+      "Lived with maximum time  56\n",
+      "Earned a total of reward equal to  1119.9867235500346\n",
+      "Lived with maximum time  6\n",
+      "Earned a total of reward equal to  99.99900274529449\n",
+      "We had a loss equal to  24369.516\n",
+      "Lived with maximum time  91\n",
+      "Earned a total of reward equal to  1799.9825665398848\n",
+      "Lived with maximum time  47\n",
+      "Earned a total of reward equal to  919.9873536471537\n",
+      "We had a loss equal to  197397.73\n",
+      "Lived with maximum time  2\n",
+      "Earned a total of reward equal to  19.999789920293725\n",
       "Lived with maximum time  1\n",
       "Earned a total of reward equal to  0.0\n",
-      "We had a loss equal to  114670.27\n",
-      "Lived with maximum time  106\n",
-      "Earned a total of reward equal to  2099.9715911363296\n",
-      "Lived with maximum time  20\n",
-      "Earned a total of reward equal to  379.9963742978001\n",
-      "Lived with maximum time  13\n",
-      "Earned a total of reward equal to  239.99723063847432\n",
-      "Lived with maximum time  8\n",
-      "Earned a total of reward equal to  139.99848845275488\n",
-      "We had a loss equal to  266143.47\n",
-      "Lived with maximum time  7\n",
-      "Earned a total of reward equal to  119.99834602072825\n",
-      "Lived with maximum time  28\n",
-      "Earned a total of reward equal to  539.9935364605712\n",
-      "Lived with maximum time  34\n",
-      "Earned a total of reward equal to  659.9824675070619\n",
-      "We had a loss equal to  375963.38\n",
-      "Lived with maximum time  61\n",
-      "Earned a total of reward equal to  1199.9872936275622\n",
-      "Lived with maximum time  13\n",
-      "Earned a total of reward equal to  239.9969214564342\n",
-      "We had a loss equal to  1297703.2\n",
-      "Lived with maximum time  83\n",
-      "Earned a total of reward equal to  1639.9812973014007\n",
+      "Lived with maximum time  1\n",
+      "Earned a total of reward equal to  0.0\n",
+      "Lived with maximum time  1\n",
+      "Earned a total of reward equal to  0.0\n",
+      "Lived with maximum time  1\n",
+      "Earned a total of reward equal to  0.0\n",
+      "Lived with maximum time  1\n",
+      "Earned a total of reward equal to  0.0\n",
+      "Lived with maximum time  1\n",
+      "Earned a total of reward equal to  0.0\n",
+      "Lived with maximum time  10\n",
+      "Earned a total of reward equal to  179.9982348312529\n",
       "Lived with maximum time  13\n",
-      "Earned a total of reward equal to  239.9969214564342\n",
-      "Lived with maximum time  27\n",
-      "Earned a total of reward equal to  519.9888165634795\n",
+      "Earned a total of reward equal to  239.9975871017263\n",
+      "Lived with maximum time  17\n",
+      "Earned a total of reward equal to  319.9963352443193\n",
+      "We had a loss equal to  415911.16\n",
+      "Lived with maximum time  89\n",
+      "Earned a total of reward equal to  1759.9736204339242\n",
+      "Lived with maximum time  47\n",
+      "Earned a total of reward equal to  919.9896974762444\n",
+      "We had a loss equal to  895179.1\n",
+      "Lived with maximum time  42\n",
+      "Earned a total of reward equal to  819.9913871544907\n",
+      "Lived with maximum time  48\n",
+      "Earned a total of reward equal to  939.9894397616745\n",
+      "Lived with maximum time  14\n",
+      "Earned a total of reward equal to  259.99683450592977\n",
       "Saving Network\n",
       "Successfully saved network.\n"
      ]
@@ -1182,12 +1192,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
     "from grid2op.Runner import Runner\n",
-    "from grid2op.ChronicsHandler import GridStateFromFileWithForecasts, \n",
+    "from grid2op.ChronicsHandler import GridStateFromFileWithForecasts, Multifolder\n",
     "scoring_function = L2RPNReward\n",
     "\n",
     "# make a runner\n",
@@ -1211,9 +1221,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 15,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "The results for the trained agent are:\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
+      "\t\t - cumulative reward: 199.997670\n",
+      "\t\t - number of time steps completed: 10 / 10\n"
+     ]
+    }
+   ],
    "source": [
     "import shutil\n",
     "path_save=\"trained_agent_log\"\n",
@@ -1285,9 +1306,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 16,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1\t\t\tdict_env_modification_space.json\r\n",
+      "dict_action_space.json\tdict_observation_space.json\r\n"
+     ]
+    }
+   ],
    "source": [
     "!ls trained_agent_log"
    ]
@@ -1305,11 +1335,21 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 17,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "actions.npy\t\t\t  env_modifications.npy  observations.npy\r\n",
+      "agent_exec_times.npy\t\t  episode_meta.json\t _parameters.json\r\n",
+      "disc_lines_cascading_failure.npy  episode_times.json\t rewards.npy\r\n"
+     ]
+    }
+   ],
    "source": [
-    "!ls trained_agent_log/chronics"
+    "!ls trained_agent_log/1"
    ]
   },
   {
@@ -1323,11 +1363,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [],
    "source": [
-    "all_actions = np.load(os.path.join(\"trained_agent_log\", \"chronics\", \"actions.npy\"))\n",
+    "all_actions = np.load(os.path.join(\"trained_agent_log\", \"1\", \"actions.npy\"))\n",
     "li_actions = []\n",
     "for i in range(all_actions.shape[0]):\n",
     "    tmp = runner.env.action_space.from_vect(all_actions[i,:])\n",
@@ -1345,9 +1385,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 19,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "9"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "line_disc = 0\n",
     "line_reco = 0\n",
@@ -1375,11 +1426,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "0"
+      ]
+     },
+     "execution_count": 20,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "all_observations = np.load(os.path.join(\"trained_agent_log\", \"chronics\", \"observations.npy\"))\n",
+    "all_observations = np.load(os.path.join(\"trained_agent_log\", \"1\", \"observations.npy\"))\n",
     "li_observations = []\n",
     "nb_real_disc = 0\n",
     "for i in range(all_observations.shape[0]):\n",
@@ -1398,9 +1460,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Number of different actions played: 2\n"
+     ]
+    }
+   ],
    "source": [
     "actions_count = {}\n",
     "for act in li_actions:\n",
@@ -1444,7 +1514,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 40,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1465,7 +1535,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 41,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
@@ -1473,38 +1543,40 @@
      "output_type": "stream",
      "text": [
       "Successfully constructed networks.\n",
-      "Lived with maximum time  26\n",
-      "Earned a total of reward equal to  519.9942970392262\n",
-      "Lived with maximum time  3\n",
-      "Earned a total of reward equal to  39.999468684794714\n",
-      "Lived with maximum time  40\n",
-      "Earned a total of reward equal to  779.9902295991952\n",
-      "We had a loss equal to  1.8025886\n",
-      "Lived with maximum time  98\n",
-      "Earned a total of reward equal to  1939.9281935014285\n",
-      "Lived with maximum time  3\n",
-      "Earned a total of reward equal to  39.99913207206239\n",
-      "We had a loss equal to  1.8322923\n",
       "Lived with maximum time  36\n",
-      "Earned a total of reward equal to  699.9924635840933\n",
-      "Lived with maximum time  48\n",
-      "Earned a total of reward equal to  939.9867702692889\n",
+      "Earned a total of reward equal to  719.9895521483418\n",
       "Lived with maximum time  8\n",
-      "Earned a total of reward equal to  139.9982050774638\n",
+      "Earned a total of reward equal to  139.99768011521434\n",
+      "Lived with maximum time  4\n",
+      "Earned a total of reward equal to  59.99906341223206\n",
+      "We had a loss equal to  1.8023443\n",
+      "Lived with maximum time  72\n",
+      "Earned a total of reward equal to  1419.9760873213631\n",
+      "Lived with maximum time  2\n",
+      "Earned a total of reward equal to  19.999660128304583\n",
+      "Lived with maximum time  46\n",
+      "Earned a total of reward equal to  899.9869612195764\n",
+      "Lived with maximum time  17\n",
+      "Earned a total of reward equal to  319.9950273884641\n",
+      "We had a loss equal to  1.8021951\n",
+      "Lived with maximum time  41\n",
+      "Earned a total of reward equal to  799.987719729006\n",
+      "Lived with maximum time  17\n",
+      "Earned a total of reward equal to  319.9949135892812\n",
+      "Lived with maximum time  21\n",
+      "Earned a total of reward equal to  399.9938856128067\n",
+      "We had a loss equal to  1.8023629\n",
+      "Lived with maximum time  63\n",
+      "Earned a total of reward equal to  1239.9800818087667\n",
+      "Lived with maximum time  16\n",
+      "Earned a total of reward equal to  299.9951132765008\n",
       "Lived with maximum time  2\n",
-      "Earned a total of reward equal to  19.999733312160764\n",
-      "We had a loss equal to  1.8326377\n",
-      "Lived with maximum time  67\n",
-      "Earned a total of reward equal to  1319.9818394245372\n",
-      "Lived with maximum time  34\n",
-      "Earned a total of reward equal to  659.9915949543215\n",
-      "Lived with maximum time  5\n",
-      "Earned a total of reward equal to  79.99894483556265\n",
-      "We had a loss equal to  1.7758247\n",
-      "Lived with maximum time  62\n",
-      "Earned a total of reward equal to  1219.9904937657643\n",
-      "Lived with maximum time  23\n",
-      "Earned a total of reward equal to  439.9950118423079\n",
+      "Earned a total of reward equal to  19.999660128304583\n",
+      "Lived with maximum time  31\n",
+      "Earned a total of reward equal to  599.9903531318918\n",
+      "We had a loss equal to  1.8029592\n",
+      "Lived with maximum time  106\n",
+      "Earned a total of reward equal to  2099.9686713192973\n",
       "Saving Network\n",
       "Successfully saved network.\n"
      ]
@@ -1517,13 +1589,6 @@
     "trainer = TrainAgent(agent=my_agent, env=env)\n",
     "trainer.train(nb_frame)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
diff --git a/getting_started/4_StudyYourAgent.ipynb b/getting_started/4_StudyYourAgent.ipynb
index 79015833f..53a0dbb16 100644
--- a/getting_started/4_StudyYourAgent.ipynb
+++ b/getting_started/4_StudyYourAgent.ipynb
@@ -106,11 +106,11 @@
      "output_type": "stream",
      "text": [
       "The results for the evaluated agent are:\n",
-      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
-      "\t\t - cumulative reward: 199.998134\n",
-      "\t\t - number of time steps completed: 10 / 10\n",
       "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/2\n",
-      "\t\t - cumulative reward: 199.998134\n",
+      "\t\t - cumulative reward: 199.998150\n",
+      "\t\t - number of time steps completed: 10 / 10\n",
+      "\tFor chronics located at /home/donnotben/.local/lib/python3.6/site-packages/grid2op/data/test_multi_chronics/1\n",
+      "\t\t - cumulative reward: 199.998150\n",
       "\t\t - number of time steps completed: 10 / 10\n"
      ]
     }
@@ -159,8 +159,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1  dict_action_space.json\t     dict_observation_space.json\r\n",
-      "2  dict_env_modification_space.json\r\n"
+      "1  chronics\t\t   dict_env_modification_space.json\r\n",
+      "2  dict_action_space.json  dict_observation_space.json\r\n"
      ]
     }
    ],
@@ -426,9 +426,11 @@
           6,
           7,
           8,
-          9
+          9,
+          10
          ],
          "y": [
+          86.5,
           85.1,
           85.7,
           86.1,
@@ -1267,20 +1269,20 @@
        "<div>\n",
        "        \n",
        "        \n",
-       "            <div id=\"fdaa02be-58c5-4a22-8a0a-3e4a2b942cfc\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
+       "            <div id=\"56c312e8-6ad7-4425-88d7-af045a437355\" class=\"plotly-graph-div\" style=\"height:525px; width:100%;\"></div>\n",
        "            <script type=\"text/javascript\">\n",
        "                require([\"plotly\"], function(Plotly) {\n",
        "                    window.PLOTLYENV=window.PLOTLYENV || {};\n",
        "                    \n",
-       "                if (document.getElementById(\"fdaa02be-58c5-4a22-8a0a-3e4a2b942cfc\")) {\n",
+       "                if (document.getElementById(\"56c312e8-6ad7-4425-88d7-af045a437355\")) {\n",
        "                    Plotly.newPlot(\n",
-       "                        'fdaa02be-58c5-4a22-8a0a-3e4a2b942cfc',\n",
-       "                        [{\"type\": \"scatter\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9], \"y\": [85.1, 85.7, 86.1, 84.2, 84.2, 83.3, 82.0, 81.1, 79.5, 81.5]}],\n",
+       "                        '56c312e8-6ad7-4425-88d7-af045a437355',\n",
+       "                        [{\"type\": \"scatter\", \"x\": [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10], \"y\": [86.5, 85.1, 85.7, 86.1, 84.2, 84.2, 83.3, 82.0, 81.1, 79.5, 81.5]}],\n",
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-       "var gd = document.getElementById('7933b457-f118-40ce-b35c-b2857c44a82f');\n",
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@@ -3243,7 +3249,7 @@
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@@ -3257,7 +3263,7 @@
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@@ -3271,7 +3277,7 @@
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@@ -3285,7 +3291,7 @@
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@@ -3299,7 +3305,7 @@
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@@ -3313,7 +3319,7 @@
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@@ -3327,7 +3333,7 @@
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@@ -3341,7 +3347,7 @@
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@@ -3383,7 +3389,7 @@
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@@ -3397,7 +3403,7 @@
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@@ -3411,7 +3417,7 @@
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@@ -3425,7 +3431,7 @@
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@@ -3439,7 +3445,7 @@
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@@ -3453,7 +3459,7 @@
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@@ -3467,7 +3473,7 @@
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@@ -3537,7 +3543,7 @@
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@@ -3551,7 +3557,7 @@
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@@ -3565,7 +3571,7 @@
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@@ -3579,7 +3585,7 @@
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@@ -3607,7 +3613,7 @@
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@@ -3691,7 +3697,7 @@
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@@ -3705,7 +3711,7 @@
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@@ -3733,7 +3739,7 @@
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@@ -4106,7 +4112,7 @@
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@@ -5246,20 +5252,20 @@
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        "                        {\"responsive\": true}\n",
        "                    ).then(function(){\n",
        "                            \n",
-       "var gd = document.getElementById('fb56b214-8c6c-46e6-9fbf-fff9a254e175');\n",
+       "var gd = document.getElementById('112878e6-7617-47cb-ac18-471032b6634e');\n",
        "var x = new MutationObserver(function (mutations, observer) {{\n",
        "        var display = window.getComputedStyle(gd).display;\n",
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diff --git a/grid2op/Action.py b/grid2op/Action.py
index 3770282e1..3e2dedf73 100644
--- a/grid2op/Action.py
+++ b/grid2op/Action.py
@@ -285,9 +285,9 @@ def _get_array_from_attr_name(self, attr_name):
                 res = self._dict_inj[attr_name]
             else:
                 if attr_name == "prod_p" or attr_name == "prod_v":
-                    res = np.full(self.n_gen, fill_value=np.NaN, dtype=np.float)
+                    res = np.full(self.n_gen, fill_value=0., dtype=np.float)
                 elif attr_name == "load_p" or attr_name == "load_q":
-                    res = np.full(self.n_load, fill_value=np.NaN, dtype=np.float)
+                    res = np.full(self.n_load, fill_value=0., dtype=np.float)
                 else:
                     raise Grid2OpException("Impossible to find the attribute \"{}\" "
                                            "into the Action of type \"{}\"".format(attr_name, type(self)))
@@ -298,7 +298,8 @@ def _assign_attr_from_name(self, attr_nm, vect):
             super()._assign_attr_from_name(attr_nm, vect)
         else:
             if np.any(np.isfinite(vect)):
-                self._dict_inj[attr_nm] = vect
+                if np.any(vect != 0.):
+                    self._dict_inj[attr_nm] = vect
 
     def check_space_legit(self):
         self._check_for_ambiguity()
diff --git a/grid2op/Agent.py b/grid2op/Agent.py
index 7553814eb..2446f644f 100644
--- a/grid2op/Agent.py
+++ b/grid2op/Agent.py
@@ -24,7 +24,7 @@
     from .Converters import Converter, IdToAct, ToVect
     from .Exceptions import Grid2OpException
 except (ModuleNotFoundError, ImportError):
-    from ActionSpaceConverter import Converter, IdToAct, ToVect
+    from Converters import Converter, IdToAct, ToVect
     from Exceptions import Grid2OpException
 
 
@@ -272,6 +272,99 @@ def _get_tested_action(self, observation):
 
 
 class AgentWithConverter(Agent):
+    """
+    Compared to a regular Agent, these types of Agents are able to deal with a different representation of
+    :class:`grid2op.Action.Action` and :class:`grid2op.Observation.Observation`.
+
+    As any other Agents, AgentWithConverter will implement the :func:`Agent.act` method. But for them, it's slightly
+    different.
+
+    They receive in this method an observation, as an object (ie an instance of :class:`grid2op.Observation`). This
+    object can then be converted to any other object with the method :func:`AgentWithConverter.convert_obs`.
+
+    Then, this `transformed_observation` is pass to the method :func:`AgentWithConverter.my_act` that is supposed
+    to be defined for each agents. This function outputs an `encoded_act` which can be whatever you want to be.
+
+    Finally, the `encoded_act` is decoded into a proper action, object of class :class:`grid2op.Action.Action`,
+    thanks to the method :func:`AgentWithConverter.convert_act`.
+
+    This allows, for example, to represent actions as integers to train more easily standard discrete control algorithm
+    used to solve atari games for example.
+
+    **NB** It is possible to define :func:`AgentWithConverter.convert_obs` and :func:`AgentWithConverter.convert_act`
+     or to define a :class:`grid2op.Converters.Converter` and feed it to the `action_space_converter` parameters
+     used to initialise the class. The second option is preferred, as the :attr:`AgentWithConverter.action_space`
+     will then directly be this converter. Such an Agent will really behave as if the actions are encoded the way he
+     wants.
+
+    Examples
+    --------
+    For example, imagine an Agent uses a neural networks to take its decision.
+
+    Suppose also that, after some
+    features engineering, it's best for the neural network to use only the load active values
+    (:attr:`grid2op.Observation.Observation.load_p`) and the sum of the
+    relative flows (:attr:`grid2op.Observation.Observation.rho`) with the active flow
+    (:attr:`grid2op.Observation.Observation.p_or`) [**NB** that agent would not make sense a priori, but who knows]
+
+    Suppose that this neural network can be accessed with a class `AwesomeNN` (not available...) that can
+    predict some actions. It can be loaded with the "load" method and make predictions with the
+    "predict" method.
+
+    For the sake of the examples, we will suppose that this agent only predicts powerline status (so 0 or 1) that
+    are represented as vector. So we need to take extra care to convert this vector from a numpy array to a valid
+    action.
+
+    This is done below:
+
+
+    .. code-block:: python
+
+        import grid2op
+        import AwesomeNN # this does not exists!
+        # create a simple environment
+        env = grid2op.make()
+
+        # define the class above
+        class AgentCustomObservation(AgentWithConverter):
+            def __init__(self, action_space, path):
+                AgentWithConverter.__init__(self, action_space)
+                self.my_neural_network = AwesomeNN()
+                self.my_neural_networl.load(path)
+
+            def convert_obs(self, observation):
+                # convert the observation
+                return np.concatenate((observation.load_p, observation.rho + observation.p_or))
+
+            def convert_act(self, encoded_act):
+                # convert back the action, output from the NN "self.my_neural_network"
+                # to a valid action
+                act = self.action_space({"set_status": encoded_act})
+
+            def my_act(self, transformed_observation, reward, done=False):
+                act_predicted = self.my_neural_network(transformed_observation)
+                return act_predicted
+
+
+        # make the agent that behaves as expected.
+        my_agent = AgentCustomObservation(action_space=env.action_space, path=".")
+
+        # this agent is perfectly working :-) You can use it as any other agents.
+
+
+    Attributes
+    ----------
+    action_space_converter: :class:`grid2op.Converters.Converter`
+        The converter that is used to represents the Agent action space. Might be set to ``None`` if not initialized
+
+    init_action_space: :class:`grid2op.Action.HelperAction`
+        The initial action space. This corresponds to the action space of the :class:`grid2op.Environment.Environment`.
+
+    action_space: :class:`grid2op.Converters.HelperAction`
+        If a converter is used, then this action space represents is this converter. The agent will behave as if
+        the action space is directly encoded the way it wants.
+
+    """
     def __init__(self, action_space, action_space_converter=None, **kwargs_converter):
         self.action_space_converter = action_space_converter
         self.init_action_space = action_space
@@ -298,26 +391,110 @@ def __init__(self, action_space, action_space_converter=None, **kwargs_converter
                                        "either be a type deriving from \"Converter\", or an instance of a class"
                                        "deriving from it."
                                        "".format(action_space_converter))
-            self.action_space.init_actions(**kwargs_converter)
+            self.action_space.init_converter(**kwargs_converter)
 
     def convert_obs(self, observation):
+        """
+        This function convert the observation, that is an object of class :class:`grid2op.Observation.Observation`
+        into a representation understandable by the Agent.
+
+        For example, and agent could only want to look at the relative flows :attr:`grid2op.Observation.Observation.rho`
+        to take his decision. This is possible by  overloading this method.
+
+        This method can also be used to scale the observation such that each compononents has mean 0 and variance 1
+        for example.
+
+        Parameters
+        ----------
+        observation: :class:`grid2op.Observation.Observation`
+            Initial observation received by the agent in the :func:`Agent.act` method.
+
+        Returns
+        -------
+        res: ``object``
+            Anything that will be used by the Agent to take decisions.
+
+        """
         return self.action_space.convert_obs(observation)
 
-    def convert_act(self, act):
-        return self.action_space.convert_act(act)
+    def convert_act(self, encoded_act):
+        """
+        This function will convert an "ecnoded action" that be of any types, to a valid action that can be ingested
+        by the environment.
+
+        Parameters
+        ----------
+        encoded_act: ``object``
+            Anything that represents an action.
+
+        Returns
+        -------
+        act: :grid2op.Action.Action`
+            A valid actions, represented as a class, that corresponds to the encoded action given as input.
+
+        """
+        return self.action_space.convert_act(encoded_act)
 
     def act(self, observation, reward, done=False):
-        convert_obs = self.convert_obs(observation)
-        act = self.my_act(convert_obs, reward, done)
-        return self.convert_act(act)
+        """
+        Standard method of an :class:`Agent`. There is no need to overload this function.
+
+        Parameters
+        ----------
+        observation: :class:`grid2op.Observation.Observation`
+            The current observation of the :class:`grid2op.Environment.Environment`
+
+        reward: ``float``
+            The current reward. This is the reward obtained by the previous action
+
+        done: ``bool``
+            Whether the episode has ended or not. Used to maintain gym compatibility
+
+        Returns
+        -------
+        res: :class:`grid2op.Action.Action`
+            The action chosen by the bot / controler / agent.
+
+        """
+        transformed_observation = self.convert_obs(observation)
+        encoded_act = self.my_act(transformed_observation, reward, done)
+        return self.convert_act(encoded_act)
 
     @abstractmethod
     def my_act(self, transformed_observation, reward, done=False):
+        """
+        This method should be overide if this class is used. It is an "abstract" method.
+
+        If someone wants to make a agent that handles different kinds of actions an observation.
+
+        Parameters
+        ----------
+        transformed_observation: ``object``
+            Anything that will be used to create an action. This is the results to the call of
+            :func:`AgentWithConverter.convert_obs`. This is likely a numpy array.
+
+        reward: ``float``
+            The current reward. This is the reward obtained by the previous action
+
+        done: ``bool``
+            Whether the episode has ended or not. Used to maintain gym compatibility
+
+        Returns
+        -------
+        res: ``object``
+            A representation of an action in any possible format. This action will then be ingested and formatted into
+            a valid action with the :func:`AgentWithConverter.convert_act` method.
+
+        """
         transformed_action = None
         return transformed_action
 
 
 class RandomAgent(AgentWithConverter):
+    """
+    This agent acts randomnly on the powergrid. It uses the :class:`grid2op.Converters.IdToAct` to compute all the
+    possible actions available for the environment. And then chooses a random one among all these.
+    """
     def __init__(self, action_space, action_space_converter=IdToAct, **kwargs_converter):
         AgentWithConverter.__init__(self, action_space, action_space_converter, **kwargs_converter)
 
@@ -326,6 +503,12 @@ def my_act(self, transformed_observation, reward, done=False):
 
 
 class MLAgent(AgentWithConverter):
+    """
+    This agent allows to handle only vectors. The "my_act" function will return "do nothing" action (so it needs
+    to be override)
+
+    In this class, the "my_act" is expected to return a vector that can be directly converted into a valid action.
+    """
     def __init__(self, action_space, action_space_converter=ToVect, **kwargs_converter):
         AgentWithConverter.__init__(self, action_space, action_space_converter, **kwargs_converter)
         self.do_nothing_vect = action_space({}).to_vect()
@@ -351,86 +534,3 @@ def convert_from_vect(self, act):
         res.from_vect(act)
         return res
 
-# class MLAgent(Agent):
-#     """
-#     This Agent class has the particularity to handle only vector representation of :class:`grid2op.Action.Action` and
-#     :class:`grid2op.Observation.Observation`. It is particularly suited for building Machine Learning Agents.
-#
-#     Attributes
-#     ----------
-#     do_nothing_vect: ``numpy.ndarray``, dtype:np.float
-#         The representation of the "do nothing" Action as a numpy vector.
-#
-#     """
-#     def __init__(self, action_space):
-#         Agent.__init__(self, action_space)
-#         self.do_nothing_vect = action_space({}).to_vect()
-#
-#     def convert_from_vect(self, act):
-#         """
-#         Helper to convert an action, represented as a numpy array as an :class:`grid2op.Action` instance.
-#
-#         Parameters
-#         ----------
-#         act: ``numppy.ndarray``
-#             An action cast as an :class:`grid2op.Action.Action` instance.
-#
-#         Returns
-#         -------
-#         res: :class:`grid2op.Action.Action`
-#             The `act` parameters converted into a proper :class:`grid2op.Action.Action` object.
-#         """
-#         res = self.action_space({})
-#         res.from_vect(act)
-#         return res
-#
-#     def act(self, observation, reward, done=False):
-#         """
-#         Overloading of the method `act` to deal with vectors representation of :class:`grid2op.Observation` and
-#         :class:`grid2op.Action` rather than with class.
-#
-#         Parameters
-#         ----------
-#         observation: :class:`grid2op.Observation.Observation`
-#             The current observation of the :class:`grid2op.Environment`
-#
-#         reward: ``float``
-#             The current reward. This is the reward obtained by the previous action
-#
-#         done: ``bool``
-#             Whether the episode has ended or not. Used to maintain gym compatibility
-#
-#         Returns
-#         -------
-#         res: :class:`grid2op.Action.Action`
-#             The action chosen by the bot / controler / agent.
-#
-#         """
-#         obs = observation.to_vect()
-#         act = self._ml_act(obs, reward, done=done)
-#         return self.convert_from_vect(act)
-#
-#     def _ml_act(self, observation, reward, done=False):
-#         """
-#         The method to modify that is able to handle numpy array representation of both action and observation.
-#         It should be overidden for ML agents using the :class:`MLAgent`.
-#
-#         Parameters
-#         ----------
-#         observation: ``numppy.ndarray``
-#             The current observation of the game, represented as a numpy array vector.
-#
-#         reward: ``float``
-#             The current reward. This is the reward obtained by the previous action
-#
-#         done: ``bool``
-#             Whether the episode has ended or not. Used to maintain gym compatibility
-#
-#         Returns
-#         -------
-#         res: ``numppy.ndarray``
-#             The action taken at time t, represented as a numpy array vector.
-#         """
-#
-#         return self.do_nothing_vect
-
diff --git a/grid2op/BackendPandaPower.py b/grid2op/BackendPandaPower.py
index 470f331d3..67f4f0255 100644
--- a/grid2op/BackendPandaPower.py
+++ b/grid2op/BackendPandaPower.py
@@ -149,7 +149,10 @@ def load_grid(self, path=None, filename=None):
         if not os.path.exists(full_path):
             raise RuntimeError("There is no powergrid at \"{}\"".format(full_path))
 
-        self._grid = pp.from_json(full_path)
+        with warnings.catch_warnings():
+            # remove deprecationg warnings for old version of pandapower
+            warnings.filterwarnings("ignore", category=DeprecationWarning)
+            self._grid = pp.from_json(full_path)
 
         # add the slack bus that is often not modeled as a generator, but i need it for this backend to work
         bus_gen_added = None
@@ -305,24 +308,10 @@ def load_grid(self, path=None, filename=None):
         add_topo["in_service"] = False
         self._grid.bus = pd.concat((self._grid.bus, add_topo))
 
-        self.prod_pu_to_kv = self._grid.bus["vn_kv"][self._grid.gen["bus"]].values
-        self.load_pu_to_kv = self._grid.bus["vn_kv"].values[self._grid.load["bus"]]
-        for i, (_, row) in enumerate(self._grid.load.iterrows()):
-            self.load_pu_to_kv[i] = self._grid.bus["vn_kv"][row["bus"]]
-        for i, (_, row) in enumerate(self._grid.gen.iterrows()):
-            self.prod_pu_to_kv[i] = self._grid.bus["vn_kv"][row["bus"]]
-
-        self.lines_or_pu_to_kv  = np.concatenate((self._grid.bus["vn_kv"][self._grid.line["from_bus"].values],
-                                self._grid.bus["vn_kv"][self._grid.trafo["hv_bus"].values]))
-        self.lines_ex_pu_to_kv = np.concatenate((self._grid.bus["vn_kv"][self._grid.line["to_bus"].values],
-                                self._grid.bus["vn_kv"][self._grid.trafo["lv_bus"].values]))
-
-        for i, (_, row) in enumerate(self._grid.line.iterrows()):
-            self.lines_or_pu_to_kv[i] = self._grid.bus["vn_kv"][row["from_bus"]]
-            self.lines_or_pu_to_kv[i] = self._grid.bus["vn_kv"][row["to_bus"]]
-        for i, (_, row) in enumerate(self._grid.trafo.iterrows()):
-            self.lines_or_pu_to_kv[i] = self._grid.bus["vn_kv"][row["hv_bus"]]
-            self.lines_or_pu_to_kv[i] = self._grid.bus["vn_kv"][row["lv_bus"]]
+        self.load_pu_to_kv = self._grid.bus["vn_kv"][self.load_to_subid].values
+        self.prod_pu_to_kv  = self._grid.bus["vn_kv"][self.gen_to_subid].values
+        self.lines_or_pu_to_kv = self._grid.bus["vn_kv"][self.line_or_to_subid].values
+        self.lines_ex_pu_to_kv = self._grid.bus["vn_kv"][self.line_ex_to_subid].values
 
         self._nb_bus_before = self.get_nb_active_bus()
 
@@ -345,7 +334,8 @@ def apply_action(self, action: Action):
         """
 
         if not isinstance(action, Action):
-            raise UnrecognizedAction("Action given to PandaPowerBackend should be of class Action and not \"{}\"".format(action.__class__))
+            raise UnrecognizedAction("Action given to PandaPowerBackend should be of class Action and not "
+                                     "\"{}\"".format(action.__class__))
 
         # change the _injection if needed
         dict_injection, change_status, switch_status, set_topo_vect, switcth_topo_vect, redispatching = action()
@@ -357,26 +347,16 @@ def apply_action(self, action: Action):
                 ok_ind = np.isfinite(val)
                 if k == "prod_v":
                     pass
-                    # continue
                     # convert values back to pu
-                    val /= self.prod_pu_to_kv # self._grid.bus["vn_kv"][self._grid.gen["bus"]].values
-                    # try:
+                    val /= self.prod_pu_to_kv  # self._grid.bus["vn_kv"][self._grid.gen["bus"]].values
                     if self._id_bus_added is not None:
                         # in this case the slack bus where not modeled as an independant generator in the
                         # original data
                         if np.isfinite(val[self._id_bus_added]):
                             # handling of the slack bus, where "2" generators are present.
                             pass
-                            # self._grid._ppc['gen'][self._iref_slack, 5] = val[self._id_bus_added]
-                            # self._grid._ppc['gen'][-1, 5] = val[self._id_bus_added]
                             self._grid["ext_grid"]["vm_pu"] = val[self._id_bus_added]
-                    # ok_ind[self._id_bus_added] = False
-                    # except:
-                    #    pdb.set_trace()
                 tmp[ok_ind] = val[ok_ind]
-                # if k == "prod_v":
-                #    pass
-                #    pdb.set_trace()
             else:
                 warn = "The key {} is not recognized by PandaPowerBackend when setting injections value.".format(k)
                 warnings.warn(warn)
@@ -426,20 +406,14 @@ def apply_action(self, action: Action):
                         if nb_bus_before > nb_bus_now:
                             # i must deactivate the unused bus
                             self._grid.bus["in_service"][sub_id + self.n_sub] = False
-                            # print("I deactivated bus {} [before: {}; after {}]".format(sub_id,nb_bus_before,nb_bus_now))
                         elif nb_bus_before < nb_bus_now:
                             # i must activate the new bus
                             self._grid.bus["in_service"][sub_id + self.n_sub] = True
-                            # print("I reactivated second bus of substation {} [before: {}; after {}]".format(sub_id,nb_bus_before,nb_bus_now))
 
                         # now assign the proper bus to each element
                         for i, (table, col_name, row_id) in enumerate(self._what_object_where[sub_id]):
                             self._grid[table][col_name].iloc[row_id] = sub_id if actual_topo[i] == 1 else sub_id + self.n_sub
 
-                            #if table == "line" or table == "trafo":
-                            #    # I connect it if it was disconnected
-                            #    self._grid[table]["in_service"].iloc[row_id] = True
-                            #    print("I reconnected a powerline")
                     beg_ += nb_obj
 
         # change line status if needed
@@ -467,7 +441,8 @@ def apply_action(self, action: Action):
                         bus_or = set_topo_vect[self.line_or_pos_topo_vect[i]]
                         bus_ex = set_topo_vect[self.line_ex_pos_topo_vect[i]]
                         if bus_ex == 0 or bus_or == 0:
-                            raise InvalidLineStatus("Line {} was disconnected. The action switched its status, without providing buses to connect it on both ends.".format(i))
+                            raise InvalidLineStatus("Line {} was disconnected. The action switched its status, "
+                                                    "without providing buses to connect it on both ends.".format(i))
                         # reconnection has then be handled in the topology
                         df["in_service"].iloc[tmp] = True
 
@@ -510,16 +485,12 @@ def runpf(self, is_dc=False):
                     # sometimes pandapower does not detect divergence and put Nan.
                     raise pp.powerflow.LoadflowNotConverged
 
-                # if self._grid.res_load.isnull().values.any():
-                #     # TODO see if there is a better way here
-                #     # some loads are disconnected: it's a game over case!
-                #     raise pp.powerflow.LoadflowNotConverged
-
                 self.load_p, self.load_q, self.load_v = self._loads_info()
-                if not np.all(np.isfinite(self.load_v)):
-                    # TODO see if there is a better way here
-                    # some loads are disconnected: it's a game over case!
-                    raise pp.powerflow.LoadflowNotConverged
+                if not is_dc:
+                    if not np.all(np.isfinite(self.load_v)):
+                        # TODO see if there is a better way here
+                        # some loads are disconnected: it's a game over case!
+                        raise pp.powerflow.LoadflowNotConverged
 
                 # I retrieve the data once for the flows, so has to not re read multiple dataFrame
                 self.p_or = self._aux_get_line_info("p_from_mw", "p_hv_mw")
@@ -643,7 +614,7 @@ def generators_info(self):
     def _loads_info(self):
         load_p = 1. * self._grid.res_load["p_mw"].values
         load_q = 1. * self._grid.res_load["q_mvar"].values
-        load_v = self._grid.res_bus["vm_pu"].values[self._grid.load["bus"]] * self.load_pu_to_kv
+        load_v = self._grid.res_bus["vm_pu"][self.load_to_subid].values * self.load_pu_to_kv
         return load_p, load_q, load_v
 
     def loads_info(self):
@@ -658,7 +629,7 @@ def lines_ex_info(self):
     def shunt_info(self):
         shunt_p = copy.deepcopy(self._grid.res_shunt["p_mw"].values)
         shunt_q = copy.deepcopy(self._grid.res_shunt["q_mvar"].values)
-        shunt_v = self._grid.res_bus["vm_pu"].values[self._grid.shunt["bus"]] * self._grid.bus["vn_kv"].values[self._grid.shunt["bus"]]
+        shunt_v = self._grid.res_bus["vm_pu"][self._grid.shunt["bus"]] * self._grid.bus["vn_kv"].values[self._grid.shunt["bus"]]
         shunt_bus = self._grid.shunt["bus"].values
         return shunt_p, shunt_q, shunt_v, shunt_bus
 
diff --git a/grid2op/Converters.py b/grid2op/Converters.py
index 860efeea0..92e1d9c13 100644
--- a/grid2op/Converters.py
+++ b/grid2op/Converters.py
@@ -1,3 +1,40 @@
+"""
+In this module of grid2op, the "converters" are defined.
+
+A converter is a specific class of :class:`grid2op.Action.HelperAction` (ie of Action Space) that allows the agent to
+manipulate this action to have a different representation of it.
+
+For example, suppose we are dealing with TopologyAction (only manipulating the graph of the powergrid). This is a
+discrete "action space". Often, it's custom to deal with such action space by enumerating all actions, and then assign
+to all valid actions a unique ID.
+
+This can be done easily with the :class:`IdToAct` class.
+
+More concretely, the diagram of an agent is:
+
+i) receive an observation (in a form of an object of class :class:`grid2op.Observation.Observation`)
+ii) implement the :func:`grid2op.Agent.Agent.act` taking as input an :class:`grid2op.Observation.Observation` and
+    returning an :class:`grid2op.Action.Action`
+iii) this :class:`grid2op.Action.Action` is then digested by the environment
+
+Introducing some converters lead to the following:
+
+i) receive an observation (:class:`grid2op.Observation.Observation`)
+ii) the transformer automatically (using :func:`Converter.convert_obs`) to a `transformed observation`
+iii) implement the function :func:`grid2op.Agent.AgentWithConverter.my_act` that takes as input
+     a `transformed observation` and returns an `encoded action`
+iv) the transformer automatically transforms back the `encoded action` into a proper :class:`grid2op.Action.Action`
+v) this :class:`grid2op.Action.Action` is then digested by the environment
+
+This simple mechanism allows people to focus on iii) above (typically implemented with artificial neural networks)
+without having to worry each time about the complex representations of actions and observations.
+
+More details and a concrete example is given in the documentation of the class
+:class:`grid2op.Agent.AgentWithConverter`.
+
+Some examples of converters are given in :class:`IdToAct` and :class:`ToVect`.
+"""
+
 import numpy as np
 import itertools
 
@@ -10,31 +47,130 @@
 
 import pdb
 
+# TODO more exhaustive documentation and tests.
+
 
 class Converter(HelperAction):
+    """
+    This Base class should be use to implement any converter. If for some reasons
+    """
     def __init__(self, action_space):
         HelperAction.__init__(self, action_space, action_space.legal_action, action_space.subtype)
         self.space_prng = action_space.space_prng
         self.seed_used = action_space.seed_used
 
-    def init_actions(self):
+    def init_converter(self, **kwargs):
         pass
 
     def convert_obs(self, obs):
-        return obs
+        """
+        This function is used to convert an observation into something that is easier to manipulate.
+
+        Parameters
+        ----------
+        obs: :class:`grid2op.Observation.Observation`
+            The input observation.
 
-    def convert_act(self, act):
-        return act
+        Returns
+        -------
+
+        transformed_obs: ``object``
+            An different representation of the input observation, typically represented as a 1d vector that can be
+            processed by a neural networks.
+
+        """
+        transformed_obs = obs
+        return transformed_obs
+
+    def convert_act(self, encoded_act):
+        """
+        This function will transform the action, encoded somehow (for example identified by an id, represented by
+        an integer) to a valid actions that can be processed by the environment.
+
+        Parameters
+        ----------
+        encoded_act: ``object``
+            Representation of an action, as a vector or an integer etc.
+
+        Returns
+        -------
+        regular_act: :class:`grid2op.Action.Action`
+            The action corresponding to the `encoded_action` above converted into a format that can be processed
+            by the environment.
+
+        """
+        regular_act = encoded_act
+        return regular_act
 
 
 class IdToAct(Converter):
+    """
+    This type of converter allows to represent action with unique id. Instead of manipulating complex objects, it allows
+    to manipulate only positive integer.
+
+    The list of all actions can either be the list of all possible unary actions (see below for a complete
+    description) or by a given pre computed list.
+
+    A "unary action" is an action that consists only in acting on one "concept" it includes:
+
+    - disconnecting a single powerline
+    - reconnecting a single powerline and connect it to bus xxx on its origin end and yyy on its extremity end
+    - changing the topology of a single substation
+
+    Examples of non unary actions include:
+    - disconnection / reconnection of 2 or more powerlines
+    - change of the configuration of 2 or more substations
+    - disconnection / reconnection of a single powerline and change of the configration of a single substation
+
+    **NB** All the actions created automatically are unary. For the L2RPN 2019, agent could be allowed to act with non
+    unary actions, for example by disconnecting a powerline and reconfiguring a substation. This class would not
+    allow to do such action at one time step.
+
+    **NB** The actions that are initialized by default uses the "set" way and not the "change" way (see the description
+    of :class:`grid2op.Action.Action` for more information).
+
+    For each powerline, 5 different actions will be computed:
+
+    - disconnect it
+    - reconnect it and connect it to bus 1 on "origin" end ann bus 1 on "extremity" end
+    - reconnect it and connect it to bus 1 on "origin" end ann bus 2 on "extremity" end
+    - reconnect it and connect it to bus 2 on "origin" end ann bus 1 on "extremity" end
+    - reconnect it and connect it to bus 2 on "origin" end ann bus 2 on "extremity" end
+
+    Actions corresponding to all topologies are also used by default. See
+    :func:`grid2op.Action.HelperAction.get_all_unitary_topologies_set` for more information.
+
+
+    In this converter:
+
+    - `encoded_act` are positive integer, representing the index of the actions.
+    - `transformed_obs` are regular observations.
+
+    """
     def __init__(self, action_space):
         Converter.__init__(self, action_space)
         self.all_actions = []
         self.all_actions.append(super().__call__())  # add the do nothing topology
         self.n = 1
 
-    def init_actions(self, all_actions=None):
+    def init_converter(self, all_actions=None, **kwargs):
+        """
+        This function is used to initialized the converter. When the converter is created, this method should be called
+        otherwise the converter might be in an unstable state.
+
+        Parameters
+        ----------
+        all_actions: ``list``
+            The (ordered) list of all actions that the agent will be able to perform. If given a number ``i`` the
+            converter will return action ``all_actions[i]``. In the "pacman" game, this vector could be
+            ["up", "down", "left", "right"], in this case "up" would be encode by 0, "down" by 1, "left" by 2 and
+            "right" by 3. If nothing is provided, the converter will output all the unary actions possible for
+            the environment. Be careful, computing all these actions might take some time.
+
+        kwargs:
+            other keyword arguments
+
+        """
         if all_actions is None:
             self.all_actions = []
             if "_set_line_status" in self.template_act.attr_list_vect:
@@ -61,34 +197,89 @@ def init_actions(self, all_actions=None):
         self.n = len(self.all_actions)
 
     def sample(self):
+        """
+        Having define a complete set of observation an agent can do, sampling from it is now made easy.
+
+        One action amoung the n possible actions is used at random.
+
+        Returns
+        -------
+        res: ``int``
+            An id of an action.
+
+        """
         idx = self.space_prng.randint(0, self.n)
         return idx
 
-    def convert_act(self, act):
+    def convert_act(self, encoded_act):
         """
-        In this converter, we suppose that "act" is an id, that is the output of a
+        In this converter, we suppose that "encoded_act" is an id of an action stored in the
+        :attr:`IdToAct.all_actions` list.
+
+        Converting an id of an action (here called "act") into a valid action is then easy: we just need to take the
+        "act"-th element of :attr:`IdToAct.all_actions`.
 
         Parameters
         ----------
-        act: ``int``
+        encoded_act: ``int``
+            The id of the action
 
         Returns
         -------
-
+        action: :class:`grid2op.Action.Action`
+            The action corresponding to id "act"
         """
 
-        return self.all_actions[act]
+        return self.all_actions[encoded_act]
 
 
 class ToVect(Converter):
+    """
+    This converters allows to manipulate the vector representation of the actions and observations.
+
+    In this converter:
+
+    - `encoded_act` are numpy ndarray
+    - `transformed_obs` are numpy ndarray
+
+    """
     def __init__(self, action_space):
         Converter.__init__(self, action_space)
         self.do_nothing_vect = action_space({}).to_vect()
 
     def convert_obs(self, obs):
+        """
+        This converter will match the observation to a vector, using the :func:`grid2op.Observation.Observation.to_vect`
+        function.
+
+        Parameters
+        ----------
+        obs: :class:`grid2op.Observation.Observation`
+            The observation, that will be processed into a numpy ndarray vector.
+
+        Returns
+        -------
+        transformed_obs: ``numpy.ndarray``
+            The vector representation of the action.
+
+        """
         return obs.to_vect()
 
-    def convert_act(self, act):
+    def convert_act(self, encoded_act):
+        """
+        In this converter `encoded_act` is a numpy ndarray. This function transforms it back to a valid action.
+
+        Parameters
+        ----------
+        encoded_act: ``numpy.ndarray``
+            The action, representated as a vector
+
+        Returns
+        -------
+        regular_act: :class:`grid2op.Action.Action`
+            The corresponding action transformed with the :func:`grid2op.Action.Action.from_vect`.
+
+        """
         res = self.__call__({})
-        res.from_vect(act)
+        res.from_vect(encoded_act)
         return res
\ No newline at end of file
diff --git a/grid2op/Observation.py b/grid2op/Observation.py
index 4376da974..9329f8b42 100644
--- a/grid2op/Observation.py
+++ b/grid2op/Observation.py
@@ -303,50 +303,50 @@ class Observation(GridObjects):
         The current day of the week. Monday = 0, Sunday = 6
 
     prod_p: :class:`numpy.ndarray`, dtype:float
-        The active production value of each generator
+        The active production value of each generator (expressed in MW).
 
     prod_q: :class:`numpy.ndarray`, dtype:float
-        The reactive production value of each generator
+        The reactive production value of each generator (expressed in MVar).
 
     prod_v: :class:`numpy.ndarray`, dtype:float
-        The voltage magnitude of the bus to which each generator is connected
+        The voltage magnitude of the bus to which each generator is connected (expressed in V).
 
     load_p: :class:`numpy.ndarray`, dtype:float
-        The active load value of each consumption
+        The active load value of each consumption (expressed in MW).
 
     load_q: :class:`numpy.ndarray`, dtype:float
-        The reactive load value of each consumption
+        The reactive load value of each consumption (expressed in MVar).
 
     load_v: :class:`numpy.ndarray`, dtype:float
-        The voltage magnitude of the bus to which each consumption is connected
+        The voltage magnitude of the bus to which each consumption is connected (expressed in V).
 
     p_or: :class:`numpy.ndarray`, dtype:float
-        The active power flow at the origin end of each powerline
+        The active power flow at the origin end of each powerline (expressed in MW).
 
     q_or: :class:`numpy.ndarray`, dtype:float
-        The reactive power flow at the origin end of each powerline
+        The reactive power flow at the origin end of each powerline (expressed in MVar).
 
     v_or: :class:`numpy.ndarray`, dtype:float
-        The voltage magnitude at the bus to which the origin end of each powerline is connected
+        The voltage magnitude at the bus to which the origin end of each powerline is connected (expressed in V).
 
     a_or: :class:`numpy.ndarray`, dtype:float
-        The current flow at the origin end of each powerline
+        The current flow at the origin end of each powerline (expressed in A).
 
     p_ex: :class:`numpy.ndarray`, dtype:float
-        The active power flow at the extremity end of each powerline
+        The active power flow at the extremity end of each powerline (expressed in MW).
 
     q_ex: :class:`numpy.ndarray`, dtype:float
-        The reactive power flow at the extremity end of each powerline
+        The reactive power flow at the extremity end of each powerline (expressed in MVar).
 
     v_ex: :class:`numpy.ndarray`, dtype:float
-        The voltage magnitude at the bus to which the extremity end of each powerline is connected
+        The voltage magnitude at the bus to which the extremity end of each powerline is connected (expressed in V).
 
     a_ex: :class:`numpy.ndarray`, dtype:float
-        The current flow at the extremity end of each powerline
+        The current flow at the extremity end of each powerline (expressed in A).
 
     rho: :class:`numpy.ndarray`, dtype:float
         The capacity of each powerline. It is defined at the observed current flow divided by the thermal limit of each
-        powerline.
+        powerline (no unit)
 
     connectivity_matrix_: :class:`numpy.ndarray`, dtype:float
         The connectivityt matrix (if computed, or None) see definition of :func:`connectivity_matrix` for
@@ -1362,7 +1362,8 @@ class ObservationHelper(SerializableObservationSpace):
 
     rewardClass: ``type``
         Class used by the :class:`grid2op.Environment.Environment` to send information about its state to the
-        :class:`grid2op.Agent.Agent`
+        :class:`grid2op.Agent.Agent`. You can change this class to differentiate between the reward of output of
+        :func:`Observation.simulate`  and the reward used to train the Agent.
 
     action_helper_env: :class:`grid2op.Action.HelperAction`
         Action space used to create action during the :func:`Observation.simulate`
diff --git a/grid2op/Space.py b/grid2op/Space.py
index c6353a759..f7638707c 100644
--- a/grid2op/Space.py
+++ b/grid2op/Space.py
@@ -83,9 +83,21 @@ class GridObjects:
 
         - method 1 (not recommended):
 
-          i) retrieve the substation to which this object is connected (for example looking at :attr:`GridObjects.line_or_to_subid` [l_id] to know on which substation is connected the origin of powerline with id $l_id$.)
-          ii) once this substation id is known, compute which are the components of the topological vector that encodes information about this substation. For example, if the substation id `sub_id` is 4, we a) count the number of elements in substations with id 0, 1, 2 and 3 (say it's 42) we know, by definition that the substation 4 is encoded in ,:attr:`grid2op.Observation.Observation.topo_vect` starting at component 42 and b) this substations has :attr:`GridObjects.sub_info` [sub_id] elements (for the sake of the example say it's 5) then the end of the vector for substation 4 will be 42+5 = 47. Finally, we got the representation of the "local topology" of the substation 4 by looking at :attr:`grid2op.Observation.Observation.topo_vect` [42:47].
-          iii) retrieve which component of this vector of dimension 5 (remember we assumed substation 4 had 5 elements) encodes information about the origin end of the line with id `l_id`. This information is given in :attr:`GridObjects.line_or_to_sub_pos` [l_id]. This is a number between 0 and 4, say it's 3. 3 being the index of the object in the substation)
+          i) retrieve the substation to which this object is connected (for example looking at
+             :attr:`GridObjects.line_or_to_subid` [l_id] to know on which substation is connected the origin of
+             powerline with id $l_id$.)
+          ii) once this substation id is known, compute which are the components of the topological vector that encodes
+              information about this substation. For example, if the substation id `sub_id` is 4, we a) count the number
+              of elements in substations with id 0, 1, 2 and 3 (say it's 42) we know, by definition that the substation
+              4 is encoded in ,:attr:`grid2op.Observation.Observation.topo_vect` starting at component 42 and b) this
+              substations has :attr:`GridObjects.sub_info` [sub_id] elements (for the sake of the example say it's 5)
+              then the end of the vector for substation 4 will be 42+5 = 47. Finally, we got the representation of the
+              "local topology" of the substation 4 by looking at
+              :attr:`grid2op.Observation.Observation.topo_vect` [42:47].
+          iii) retrieve which component of this vector of dimension 5 (remember we assumed substation 4 had 5 elements)
+               encodes information about the origin end of the line with id `l_id`. This information is given in
+               :attr:`GridObjects.line_or_to_sub_pos` [l_id]. This is a number between 0 and 4, say it's 3. 3 being
+               the index of the object in the substation)
 
         - method 2 (not recommended): all of the above is stored (for the same powerline) in the
           :attr:`GridObjects.line_or_pos_topo_vect` [l_id]. In the example above, we will have:
@@ -120,17 +132,17 @@ class GridObjects:
     Note that if you want to model an environment with unit commitment or redispatching capabilities, you also need
     to provide the following attributes:
 
-          - :attr:`GridObjects.gen_type`
-          - :attr:`GridObjects.gen_pmin`
-          - :attr:`GridObjects.gen_pmax`
-          - :attr:`GridObjects.gen_redispatchable`
-          - :attr:`GridObjects.gen_max_ramp_up`
-          - :attr:`GridObjects.gen_max_ramp_down`
-          - :attr:`GridObjects.gen_min_uptime`
-          - :attr:`GridObjects.gen_min_downtime`
-          - :attr:`GridObjects.gen_cost_per_MW`
-          - :attr:`GridObjects.gen_startup_cost`
-          - :attr:`GridObjects.gen_shutdown_cost`
+    - :attr:`GridObjects.gen_type`
+    - :attr:`GridObjects.gen_pmin`
+    - :attr:`GridObjects.gen_pmax`
+    - :attr:`GridObjects.gen_redispatchable`
+    - :attr:`GridObjects.gen_max_ramp_up`
+    - :attr:`GridObjects.gen_max_ramp_down`
+    - :attr:`GridObjects.gen_min_uptime`
+    - :attr:`GridObjects.gen_min_downtime`
+    - :attr:`GridObjects.gen_cost_per_MW`
+    - :attr:`GridObjects.gen_startup_cost`
+    - :attr:`GridObjects.gen_shutdown_cost`
 
     These information are loaded using the :func:`grid2op.Backend.Backend.load_redispacthing_data` method.
 
@@ -276,8 +288,8 @@ class GridObjects:
         for unit commitment problems or redispacthing action.
 
     gen_cost_per_MW: :class:`numpy.ndarray`, dtype:float
-        For each generator, it gives the "operating cost", eg the cost, in terms of "used currency" for the production of
-        one MW with this generator, if it is already turned on. It's a positive real number. It's the marginal cost
+        For each generator, it gives the "operating cost", eg the cost, in terms of "used currency" for the production
+        of one MW with this generator, if it is already turned on. It's a positive real number. It's the marginal cost
         for each MW. Optional. Used
         for unit commitment problems or redispacthing action.
 
diff --git a/grid2op/__init__.py b/grid2op/__init__.py
index 16e9589de..f620c8248 100644
--- a/grid2op/__init__.py
+++ b/grid2op/__init__.py
@@ -6,7 +6,7 @@
 import os
 import pkg_resources
 
-__version__ = '0.4.3'
+__version__ = '0.5.0'
 
 __all__ = ['Action', "BackendPandaPower", "Agent", "Backend", "ChronicsHandler", "Environment", "Exceptions",
            "Observation", "Parameters", "GameRules", "Reward", "Runner", "main", "Utils", "PlotPlotly"]
diff --git a/grid2op/tests/test_Action.py b/grid2op/tests/test_Action.py
index de73b345c..77051c58b 100644
--- a/grid2op/tests/test_Action.py
+++ b/grid2op/tests/test_Action.py
@@ -52,11 +52,9 @@ def setUp(self):
                                           line_or_pos_topo_vect=np.array([ 0,  1,  4,  5,  6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38, 40, 46, 50]),
                                           line_ex_pos_topo_vect=np.array([ 3, 19,  9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42, 55, 43, 49, 53]))
         # pdb.set_trace()
-        self.helper_action = HelperAction(self.gridobj,
-                                          game_rules=self.game_rules)
+        self.helper_action = HelperAction(self.gridobj, legal_action=self.game_rules.legal_action)
 
-        self.helper_action_env = HelperAction(self.gridobj,
-                                              game_rules=self.game_rules,
+        self.helper_action_env = HelperAction(self.gridobj, legal_action=self.game_rules.legal_action,
                                               actionClass=Action)
 
         self.res = {'name_gen': ['gen_0', 'gen_1', 'gen_2', 'gen_3', 'gen_4'],
@@ -70,20 +68,20 @@ def setUp(self):
                     'sub_info': [3, 6, 4, 6, 5, 6, 3, 2, 5, 3, 3, 3, 4, 3],
                     'load_to_subid': [1, 2, 3, 4, 5, 8, 9, 10, 11, 12, 13],
                     'gen_to_subid': [0, 1, 2, 5, 7],
-                'line_or_to_subid': [0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
-                'line_ex_to_subid': [1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12, 13],
-                'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1],
-                'gen_to_sub_pos': [2, 5, 3, 5, 1],
-                'line_or_to_sub_pos': [0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
-                'line_ex_to_sub_pos': [0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
-                'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
-                'gen_pos_topo_vect': [2, 8, 12, 29, 34],
-                'line_or_pos_topo_vect': [0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38, 40, 46, 50],
-                'line_ex_pos_topo_vect': [3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42, 55, 43, 49, 53],
-                'gen_type': None, 'gen_pmin': None, 'gen_pmax': None, 'gen_redispatchable': None,
-                'gen_max_ramp_up': None, 'gen_max_ramp_down': None, 'gen_min_uptime': None, 'gen_min_downtime': None,
-                'gen_cost_per_MW': None, 'gen_startup_cost': None, 'gen_shutdown_cost': None,
-                'subtype': 'Action.Action'}
+                    'line_or_to_subid': [0, 0, 1, 1, 1, 2, 3, 3, 3, 4, 5, 5, 5, 6, 6, 8, 8, 9, 11, 12],
+                    'line_ex_to_subid': [1, 4, 2, 3, 4, 3, 4, 6, 8, 5, 10, 11, 12, 7, 8, 9, 13, 10, 12, 13],
+                    'load_to_sub_pos': [4, 2, 5, 4, 4, 4, 1, 1, 1, 2, 1],
+                    'gen_to_sub_pos': [2, 5, 3, 5, 1],
+                    'line_or_to_sub_pos': [0, 1, 1, 2, 3, 1, 2, 3, 4, 3, 1, 2, 3, 1, 2, 2, 3, 0, 0, 1],
+                    'line_ex_to_sub_pos': [0, 0, 0, 0, 1, 1, 2, 0, 0, 0, 2, 2, 3, 0, 1, 2, 2, 0, 0, 0],
+                    'load_pos_topo_vect': [7, 11, 18, 23, 28, 39, 41, 44, 47, 51, 54],
+                    'gen_pos_topo_vect': [2, 8, 12, 29, 34],
+                    'line_or_pos_topo_vect': [0, 1, 4, 5, 6, 10, 15, 16, 17, 22, 25, 26, 27, 31, 32, 37, 38, 40, 46, 50],
+                    'line_ex_pos_topo_vect': [3, 19, 9, 13, 20, 14, 21, 30, 35, 24, 45, 48, 52, 33, 36, 42, 55, 43, 49, 53],
+                    'gen_type': None, 'gen_pmin': None, 'gen_pmax': None, 'gen_redispatchable': None,
+                    'gen_max_ramp_up': None, 'gen_max_ramp_down': None, 'gen_min_uptime': None, 'gen_min_downtime': None,
+                    'gen_cost_per_MW': None, 'gen_startup_cost': None, 'gen_shutdown_cost': None,
+                    'subtype': 'Action.Action'}
 
         self.size_act = 229
 
@@ -344,7 +342,13 @@ def test_action_str(self):
         action = self.helper_action({"change_bus": {"substations_id": [(id_1, arr1)]},
                                      "set_bus": {"substations_id": [(id_2, arr2)]}})
         res = action.__str__()
-        act_str = 'This action will:\n\t - NOT change anything to the injections\n\t - NOT perform any redispatching action\n\t - NOT force any line status\n\t - NOT switch any line status\n\t - Change the bus of the following element:\n\t \t - switch bus of line (origin) 4 [on substation 1]\n\t \t - switch bus of load 0 [on substation 1]\n\t \t - switch bus of generator 1 [on substation 1]\n\t - Set the bus of the following element:\n\t \t - assign bus 1 to line (extremity) 18 [on substation 12]\n\t \t - assign bus 1 to line (origin) 19 [on substation 12]\n\t \t - assign bus 2 to load 9 [on substation 12]\n\t \t - assign bus 2 to line (extremity) 12 [on substation 12]'
+        act_str = 'This action will:\n\t - NOT change anything to the injections\n\t - NOT perform any redispatching ' \
+                  'action\n\t - NOT force any line status\n\t - NOT switch any line status\n\t - Change the bus of the ' \
+                  'following element:\n\t \t - switch bus of line (origin) 4 [on substation 1]\n\t \t - switch bus of ' \
+                  'load 0 [on substation 1]\n\t \t - switch bus of generator 1 [on substation 1]\n\t - Set the bus of ' \
+                  'the following element:\n\t \t - assign bus 1 to line (extremity) 18 [on substation 12]\n\t \t - ' \
+                  'assign bus 1 to line (origin) 19 [on substation 12]\n\t \t - assign bus 2 to load 9 ' \
+                  '[on substation 12]\n\t \t - assign bus 2 to line (extremity) 12 [on substation 12]'
         assert res == act_str
 
     def test_to_vect(self):
@@ -355,9 +359,9 @@ def test_to_vect(self):
         action = self.helper_action({"change_bus": {"substations_id": [(id_1, arr1)]},
                                      "set_bus": {"substations_id": [(id_2, arr2)]}})
         res = action.to_vect()
-        tmp = np.array([np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
-                        np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
-                        np.NaN, np.NaN, np.NaN, np.NaN, np.NaN, np.NaN,
+        tmp = np.array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
+                        0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,
+                        0., 0., 0., 0., 0., 0.,
                         0., 0., 0., 0., 0.,
                             0.,  0.,  0.,  0.,  0.,  0.,  0.,
                             0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,
diff --git a/grid2op/tests/test_Agent.py b/grid2op/tests/test_Agent.py
index d12aa4cf6..b31ea8d7e 100644
--- a/grid2op/tests/test_Agent.py
+++ b/grid2op/tests/test_Agent.py
@@ -84,9 +84,9 @@ def setUp(self):
         self.env_params = Parameters()
 
         self.env = Environment(init_grid_path=os.path.join(self.path_matpower, self.case_file),
-                          backend=self.backend,
-                          chronics_handler=self.chronics_handler,
-                          parameters=self.env_params,
+                               backend=self.backend,
+                               chronics_handler=self.chronics_handler,
+                               parameters=self.env_params,
                                names_chronics_to_backend=self.names_chronics_to_backend,
                                rewardClass=self.rewardClass)
 
@@ -135,7 +135,7 @@ def test_1_powerlineswitch(self):
     def test_2_busswitch(self):
         agent = TopologyGreedy(self.env.helper_action_player)
         i, cum_reward = self._aux_test_agent(agent, i_max=10)
-        assert i == 11, "The powerflow diverged before step 30 for greedy agent"
+        assert i == 11, "The powerflow diverged before step 10 for greedy agent"
         assert np.abs(cum_reward - 219.99795) <= self.tol_one, "The reward has not been properly computed"
 
 
diff --git a/grid2op/tests/test_PandaPowerBackend.py b/grid2op/tests/test_PandaPowerBackend.py
index f38e0b122..482c0aee4 100644
--- a/grid2op/tests/test_PandaPowerBackend.py
+++ b/grid2op/tests/test_PandaPowerBackend.py
@@ -125,10 +125,55 @@ def test_runpf(self):
         assert self.compare_vect(p_or, true_values_ac)
 
     def test_voltage_convert_powerlines(self):
-        conv = self.backend.runpf(is_dc=True)
+        # i have the correct voltages in powerlines if the formula to link mw, mvar, kv and amps is correct
+        conv = self.backend.runpf(is_dc=False)
         assert conv
 
-        pdb.set_trace()
+        p_or, q_or, v_or, a_or = self.backend.lines_or_info()
+        a_th = np.sqrt(p_or ** 2 + q_or ** 2) * 1e3 / (np.sqrt(3) * v_or)
+        assert self.compare_vect(a_th, a_or)
+
+        p_ex, q_ex, v_ex, a_ex = self.backend.lines_ex_info()
+        a_th = np.sqrt(p_ex ** 2 + q_ex ** 2) * 1e3 / (np.sqrt(3) * v_ex)
+        assert self.compare_vect(a_th, a_ex)
+
+    def test_voltages_correct_load_gen(self):
+        # i have the right voltages to generators and load, if it's the same as the voltage (correct from the above test)
+        # of the powerline connected to it.
+
+        conv = self.backend.runpf(is_dc=False)
+        load_p, load_q, load_v = self.backend.loads_info()
+        gen_p, gen__q, gen_v = self.backend.generators_info()
+        p_or, q_or, v_or, a_or = self.backend.lines_or_info()
+        p_ex, q_ex, v_ex, a_ex = self.backend.lines_ex_info()
+
+        for c_id, sub_id in enumerate(self.backend.load_to_subid):
+            l_id = np.where(self.backend.line_or_to_subid == sub_id)[0]
+            if len(l_id):
+                l_id = l_id[0]
+                assert np.abs(v_or[l_id] - load_v[c_id]) <= self.tol_one, "problem for load {}".format(c_id)
+                continue
+
+            l_id = np.where(self.backend.line_ex_to_subid == sub_id)[0]
+            if len(l_id):
+                l_id = l_id[0]
+                assert np.abs(v_ex[l_id] - load_v[c_id]) <= self.tol_one, "problem for load {}".format(c_id)
+                continue
+            assert False, "load {} has not been checked".format(c_id)
+
+        for g_id, sub_id in enumerate(self.backend.gen_to_subid):
+            l_id = np.where(self.backend.line_or_to_subid == sub_id)[0]
+            if len(l_id):
+                l_id = l_id[0]
+                assert np.abs(v_or[l_id] - gen_v[g_id]) <= self.tol_one, "problem for generator {}".format(g_id)
+                continue
+
+            l_id = np.where(self.backend.line_ex_to_subid == sub_id)[0]
+            if len(l_id):
+                l_id = l_id[0]
+                assert np.abs(v_ex[l_id] - gen_v[g_id]) <= self.tol_one, "problem for generator {}".format(g_id)
+                continue
+            assert False, "generator {} has not been checked".format(g_id)
 
     def test_copy(self):
         conv = self.backend.runpf(is_dc=False)
diff --git a/setup.py b/setup.py
index 26ef5ca86..3fb508b3f 100644
--- a/setup.py
+++ b/setup.py
@@ -8,7 +8,7 @@
 }
 
 setup(name='Grid2Op',
-      version='0.4.3',
+      version='0.5.0',
       description='An environment that allows to perform powergrid optimization.',
       long_description='Built with modularity in mind, this package allows to perform the same operations independantly of the software used to compute powerflow or method to generate grid states or forecasts.',
       classifiers=[