From 269ed85e608e2c562c315d4d9a02230c21220a46 Mon Sep 17 00:00:00 2001 From: zy13027 <68322026+zy13027@users.noreply.github.com> Date: Sat, 13 Aug 2022 00:30:10 +0800 Subject: [PATCH] Add files via upload --- .vsconfig | 93 + 50DQNAgenttrainedAgents.mat | Bin 0 -> 491730 bytes A3CAgenttrainedAgents.mat | Bin 0 -> 168313 bytes ACAgenttrainedAgents.mat | Bin 0 -> 166609 bytes AbstractGridWorld.m | 495 + ChannelBPSK.slx | Bin 0 -> 47549 bytes ChannelNoBPSK.slx | Bin 0 -> 34659 bytes ConsolidatedModel.slx | Bin 0 -> 33730 bytes ConsolidatedModelV0.slx | Bin 0 -> 39916 bytes ConsolidatedModelV1.slx | Bin 0 -> 36846 bytes ConsolidatedModelV2.slx | Bin 0 -> 27838 bytes ConsolidatedModelV2.slxc | Bin 0 -> 5090 bytes ConsolidatedModelV3.slx | Bin 0 -> 27021 bytes ConsolidatedModelV4.slx | Bin 0 -> 54588 bytes ConsolidatedModelV5.slx | Bin 0 -> 39327 bytes ConsolidatedModelV6.slx | Bin 0 -> 87379 bytes ConsolidatedModelV6.slx.original | Bin 0 -> 84233 bytes ConsolidatedModelV6.slxc | Bin 0 -> 5733 bytes ConsolidatedModelV7.slx | Bin 0 -> 84971 bytes ConsolidatedModelV7.slx.autosave | Bin 0 -> 64390 bytes CorrectModel.slxc | Bin 0 -> 5065 bytes CustomGridWorld.m | 520 + CustomGridWorldV0.m | 211 + DQNtrainedAgents.mat | Bin 0 -> 199348 bytes DemoJSCC.slx | Bin 0 -> 40017 bytes Draft.mlx | Bin 0 -> 91435 bytes DraftV0.mlx | Bin 0 -> 68479 bytes DraftV1.mlx | Bin 0 -> 93181 bytes DraftV2.mlx | Bin 0 -> 7804 bytes DraftV3.mlx | Bin 0 -> 6798 bytes DraftV4.mlx | Bin 0 -> 23958 bytes DraftV5.mlx | Bin 0 -> 7885 bytes Exported-2022-06-21-1.vssettings | 557 ++ Exported-2022-06-21.vssettings | 502 + GridWorld.asv | 501 + GridWorld.m | 501 + GridWorldV0.m | 462 + GridWorldV1.m | 504 + Multi Agent.mat | Bin 0 -> 281 bytes PGAgenttrainedAgents.mat | Bin 0 -> 141148 bytes PPOAgenttrainedAgents.mat | Bin 0 -> 187731 bytes ReinforcementLearningDesignerSession.mat | Bin 0 -> 3603 bytes ResetFcn.mlx | Bin 0 -> 3610 bytes act1Conv.m | 20 + createStateNames.m | 14 + customTrainingLoop.mlx | Bin 0 -> 6365 bytes dc2bi.m | 9 + ddc2bi.m | 9 + deconvert.mlx | Bin 0 -> 2926 bytes doc_bernoulli_gen_example.slx | Bin 0 -> 29187 bytes exp.slxc | Bin 0 -> 5059 bytes expri.slx | Bin 0 -> 24475 bytes expri.slxc | Bin 0 -> 5058 bytes expri0.slx | Bin 0 -> 24474 bytes replay_pid13388.log | 10948 +++++++++++++++++++++ resetMap.m | 17 + rlAreaCoverageAgents.mat | Bin 0 -> 3378166 bytes sim_and_train_differences.m | 2 + simout2dec.mlx | Bin 0 -> 3564 bytes simouttodec.mlx | Bin 0 -> 3559 bytes trial.mlx | Bin 0 -> 4906 bytes 61 files changed, 15365 insertions(+) create mode 100644 .vsconfig create mode 100644 50DQNAgenttrainedAgents.mat create mode 100644 A3CAgenttrainedAgents.mat create mode 100644 ACAgenttrainedAgents.mat create mode 100644 AbstractGridWorld.m create mode 100644 ChannelBPSK.slx create mode 100644 ChannelNoBPSK.slx create mode 100644 ConsolidatedModel.slx create mode 100644 ConsolidatedModelV0.slx create mode 100644 ConsolidatedModelV1.slx create mode 100644 ConsolidatedModelV2.slx create mode 100644 ConsolidatedModelV2.slxc create mode 100644 ConsolidatedModelV3.slx create mode 100644 ConsolidatedModelV4.slx create mode 100644 ConsolidatedModelV5.slx create mode 100644 ConsolidatedModelV6.slx create mode 100644 ConsolidatedModelV6.slx.original create mode 100644 ConsolidatedModelV6.slxc create mode 100644 ConsolidatedModelV7.slx create mode 100644 ConsolidatedModelV7.slx.autosave create mode 100644 CorrectModel.slxc create mode 100644 CustomGridWorld.m create mode 100644 CustomGridWorldV0.m create mode 100644 DQNtrainedAgents.mat create mode 100644 DemoJSCC.slx create mode 100644 Draft.mlx create mode 100644 DraftV0.mlx create mode 100644 DraftV1.mlx create mode 100644 DraftV2.mlx create mode 100644 DraftV3.mlx create mode 100644 DraftV4.mlx create mode 100644 DraftV5.mlx create mode 100644 Exported-2022-06-21-1.vssettings create mode 100644 Exported-2022-06-21.vssettings create mode 100644 GridWorld.asv create mode 100644 GridWorld.m create mode 100644 GridWorldV0.m create mode 100644 GridWorldV1.m create mode 100644 Multi Agent.mat create mode 100644 PGAgenttrainedAgents.mat create mode 100644 PPOAgenttrainedAgents.mat create mode 100644 ReinforcementLearningDesignerSession.mat create mode 100644 ResetFcn.mlx create mode 100644 act1Conv.m create mode 100644 createStateNames.m create mode 100644 customTrainingLoop.mlx create mode 100644 dc2bi.m create mode 100644 ddc2bi.m create mode 100644 deconvert.mlx create mode 100644 doc_bernoulli_gen_example.slx create mode 100644 exp.slxc create mode 100644 expri.slx create mode 100644 expri.slxc create mode 100644 expri0.slx create mode 100644 replay_pid13388.log create mode 100644 resetMap.m create mode 100644 rlAreaCoverageAgents.mat create mode 100644 sim_and_train_differences.m create mode 100644 simout2dec.mlx create mode 100644 simouttodec.mlx create mode 100644 trial.mlx diff --git a/.vsconfig b/.vsconfig new file mode 100644 index 0000000..dc50b7c --- /dev/null +++ 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-0,0 +1,495 @@ +classdef AbstractGridWorld < rl.env.AbstractMDP + %GridWorld Creates a grid world + % env = rl.env.GridWorld(m,n) + % + + % Copyright 2018-2019 The MathWorks, Inc. + + properties (SetAccess = immutable) + + % GridSize + % [m,n] vector where m and n are the number of rows and columns of + % the grid world, respectively. + GridSize + + end + + %% Dependent Properties + properties (Dependent) + + % CurrentState + % String with name of current state + CurrentState string + + % States + % String vector of the state names + States string + + % Actions + % String vector with the action names + Actions string + + % T + % State Transisition Matrix T(s,s',a) = P(s'|s,a) + T + + % R + % Reward Transisition Matrix r = R(s,s',a) + R + + % ObstacleStates + % String vector with the state names which can not be reached in + % the grid world. + ObstacleStates string + + % TerminalStates + % String vector with the state names which are terminal in the grid + % world. + TerminalStates string + + end + + %% Protected Properties + properties (Access = protected) + + % Obstacle states of the MDP + ObstacleStates_ = string.empty(0,1) + + end + + %% Hidden Properties + properties (Hidden=true) + + % Border + % True if edges moves are not allowed + Border = true; + + % Handle to the GridWorldVisualizer + Viewer + + end + + + %% Public Methods + methods + + function obj = AbstractGridWorld(m,n,Moves) + % GridWorld Construct an m by n grid world with m rows and n + % columns + narginchk(2,3) + + if ~isnumeric(m) || ~isnumeric(n) || (rem(m,1) ~= 0) || (rem(n,1) ~= 0) + % REVISIT + error(message('rl:env:GWValidGridDims')) + end + + if (nargin) == 2 + % Define action space + Actions = ["N";"S";"E";"W"]; + else + if strcmpi(Moves,'Standard') + Actions = ["N";"S";"E";"W"]; + elseif strcmpi(Moves,'Kings') + Actions = ["N";"S";"E";"W";"NE";"NW";"SE";"SW"]; + else + error(message('rl:env:GWValidMovesInput')) + end + end + % Define state names + StateNames = rl.env.GridWorld.createStateNames(m,n); + % Call super-constructor + obj = obj@rl.env.AbstractMDP(StateNames,Actions); + % Cache grid size + obj.GridSize = [m,n]; + % Initialize state transition matrix + initializeStateTransitions(obj) + end + + function T = getStateTransition(obj,Actions) + % Get state transisition matrix + % T = getStateTransition(obj) + % T = getStateTransition(obj,Action) + if nargin == 1 + T = getStateTransition_(obj); + else + T = getStateTransition_(obj,Actions); + end + end + + function RT = getRewardTransition(obj,Action) + if nargin == 1 + RT = getRewardTransition_(obj); + else + RT = getRewardTransition_(obj,Action); + end + end + + function [S,R,isTerm,loggedsig] = move(obj,Action) + S0 = obj.CurrentState; + if isValidAction(obj,S0,Action) + [S,R,isTerm] = move_(obj,Action); + else + error(message('rl:env:MDPInvalidAction')); + end + loggedsig = []; + end + + function showViewer(obj) + % showViewer(env) opens the GridWorld Viewer + obj.Viewer = rl.env.GridWorldVisualizer(obj.GridSize,[]); + setTerminalStates(obj.Viewer,obj.TerminalStates) + setObstacles(obj.Viewer,obj.ObstacleStates) + updateViewer(obj) + addlistener(obj,'CurrentStateChanged',@(es,ed) updateViewer(obj)); + end + + function updateViewer(obj) + CS = obj.CurrentState_; + CS = regexprep(regexprep(CS,"("',"["),")","]"); + obj.Viewer.setCurrentState(eval(CS)); + end + + function updateStateTranstionForObstacles(obj) + ST = obj.StateTransitions_; + m = obj.GridSize(1); + n = obj.GridSize(2); + + for ct = 1:numel(obj.ObstacleStates) + % Obstacle + idxO = state2idx(obj,obj.ObstacleStates(ct)); + + % N Action + idxAct = 1; + idxS1 = find(ST(:,idxO,idxAct)); + for ct1 = 1:numel(idxS1) + if idxO+1 < m*n + ST(idxS1(ct1),idxO+1,idxAct) = ... + ST(idxS1(ct1),idxO+1,idxAct) + ST(idxS1(ct1),idxO,idxAct); + ST(idxS1(ct1),idxO,idxAct) = 0; + end + end + + % S Action + idxAct = 2; + idxS1 = find(ST(:,idxO,idxAct)); + for ct1 = 1:numel(idxS1) + if idxO-1 > 0 + ST(idxS1(ct1),idxO-1,idxAct) = ... + ST(idxS1(ct1),idxO-1,idxAct) + ST(idxS1(ct1),idxO,idxAct); + ST(idxS1(ct1),idxO,idxAct) = 0; + end + end + + + % E Action + idxAct = 3; + idxS1 = find(ST(:,idxO,idxAct)); + for ct1 = 1:numel(idxS1) + if idxO-m > 0 + ST(idxS1(ct1),idxO-m,idxAct) = ... + ST(idxS1(ct1),idxO-m,idxAct) + ST(idxS1(ct1),idxO,idxAct); + ST(idxS1(ct1),idxO,idxAct) = 0; + end + end + + % W Action + idxAct = 4; + idxS1 = find(ST(:,idxO,idxAct)); + for ct1 = 1:numel(idxS1) + if idxO+m < m*n + ST(idxS1(ct1),idxO+m,idxAct) = ... + ST(idxS1(ct1),idxO+m,idxAct) + ST(idxS1(ct1),idxO,idxAct); + ST(idxS1(ct1),idxO,idxAct) = 0; + end + end + end + + obj.StateTransitions_=ST; + end + + + function State = reset(obj,State) + if nargin == 1 + State = getRandomInitialState(obj); + else + PotentialStates = setdiff(obj.States,obj.ObstacleStates); + PotentialStates = setdiff(PotentialStates,obj.TerminalStates); + if ~ismember(State, PotentialStates) + % REVISIT do we want to change wording of error message + error(message('rl:env:MDPInvalidState')) + end + end + obj.CurrentState = State; + end + end + + + %% Set/Get Methods + methods + % CurrentState + function set.CurrentState(obj,State) + % Set Current State + + % Validate that its a valid state and not an obstacle state + obj.CurrentState_ = State; + end + + function State = get.CurrentState(obj) + % Get Current State + State = obj.CurrentState_; + end + + % States + function set.States(obj,States) + % Set States + % REVISIT + error(message('rl:env:GWCannotSetStates')) + end + + function States = get.States(obj) + % Get States + States = obj.States_; + end + + % Actions + function set.Actions(obj,Actions) + % Set Actions + % REVISIT + error(message('rl:env:GWCannotSetActions')) + end + + function Actions = get.Actions(obj) + % Get Actions + Actions = obj.Actions_; + end + + % T + function T = get.T(obj) + % Get T + T = getStateTransition(obj); + end + + function set.T(obj,T) + % Set T + validateT(obj,T) + setStateTransition_(obj,T); + end + + %R + function R = get.R(obj) + % Get R + R = getRewardTransition(obj); + end + + function set.R(obj,R) + % Set R + validateR(obj,R) + setRewardTransition_(obj,R); + end + + % ObstacleStates + function set.ObstacleStates(obj,StateNames) + for ct = 1:numel(StateNames) + if isTerminalState(obj,StateNames(ct)) || ~isState(obj,StateNames(ct)) + % REVISIT + error(message('rl:env:GWInvalidObstacleState')) + end + end + obj.ObstacleStates_ = unique(StateNames); + end + + function ObstacleStates = get.ObstacleStates(obj) + ObstacleStates = obj.ObstacleStates_; + end + + % TerminalStates + function set.TerminalStates(obj,StateNames) + for ct = 1:numel(StateNames) + if isObstacleState(obj,StateNames(ct)) || ~isState(obj,StateNames(ct)) + % REVISIT + error(message('rl:env:GWInvalidTerminalState')) + end + end + obj.TerminalStates_ = unique(StateNames); + end + + function TeriminalState = get.TerminalStates(obj) + TeriminalState = obj.TerminalStates_; + end + + end + + + %% Protected Methods + methods (Access = protected) + + function initializeStateTransitions(obj) + for ct = 1:numel(obj.Actions_) + ActionName = obj.Actions_(ct); + ST = createStateTransition(obj,ActionName); + setStateTransition_(obj,ST,ActionName) + end + end + + function ST = createStateTransition(obj,Action) + m = obj.GridSize(1); + n = obj.GridSize(2); + ST = zeros(m*n,m*n); + switch Action + case "N" + % Move North + for c = 1:n + r = 1; + if obj.Border + ST(r+(c-1)*m,r+(c-1)*m) = 1; + else + ST(r+(c-1)*m,c*m) = 1; + end + for r = 2:m + ST(r+(c-1)*m,(r-1)+(c-1)*m) = 1; + end + end + case "S" + % Move South + for c = 1:n + for r = 1:m-1 + ST(r+(c-1)*m,(r+1)+(c-1)*m) = 1; + end + r = m; + if obj.Border + ST(r+(c-1)*m,r+(c-1)*m) = 1; + else + ST(c*m,1+(c-1)*m) = 1; + end + end + case "E" + % Move East + for r = 1:m + for c = 1:n-1 + ST(r+(c-1)*m,r+(c+0)*m) = 1; + end + c = n; + if obj.Border + ST(r+(c-1)*m,r+(c-1)*m) = 1; + else + ST(r+(c-1)*m,r) = 1; + end + end + case "W" + % Move West + for r = 1:m + c = 1; + if obj.Border + ST(r,r) = 1; + else + ST(r,r+(n-1)*m) = 1; + end + for c = 2:n + ST(r+(c-1)*m,r+(c-2)*m) = 1; + end + end + case "NW" + % Move North West + for c = 2:n + for r = 2:m + ST(r+(c-1)*m,(r-1)+(c-2)*m) = 1; + end + end + if obj.Border + for c = 1:n %N + r = 1; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + for r = 1:m %W + ST(r,r) = 1; + end + end + case "SW" + % Move South West + for c = 2:n + for r = 1:m-1 + ST(r+(c-1)*m,(r+1)+(c-2)*m) = 1; + end + end + if obj.Border + for c = 1:n %S + r = m; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + for r = 1:m %W + ST(r,r) = 1; + end + end + case "NE" + % Move North East + for c = 1:n-1 + for r = 2:m + ST(r+(c-1)*m,(r-1)+(c+0)*m) = 1; + end + end + if obj.Border + for c = 1:n %N + r = 1; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + for r = 1:m %E + c = n; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + end + case "SE" + % Move South East + for c = 1:n-1 + for r = 1:m-1 + ST(r+(c-1)*m,(r+1)+(c+0)*m) = 1; + end + end + if obj.Border + for c = 1:n %S + r = m; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + for r = 1:m %E + c = n; + ST(r+(c-1)*m,r+(c-1)*m) = 1; + end + end + end + end + + function b = isObstacleState(obj,State) + % Check if State is an ObstacleState + b = any(strcmp(State, obj.ObstacleStates)); + end + + function State = getRandomInitialState(obj) + % get random initial state that is not an obstacle or terminal + % state + PotentialStates = setdiff(setdiff(obj.States,obj.ObstacleStates),obj.TerminalStates); + % Randomly select one of the potential states + State = PotentialStates(randi(numel(PotentialStates))); + + end + + end + + + %% Static Methods + methods (Static = true) + + function Names = createStateNames(m,n) + % Create array of state name "[m,n]" + + Names = ""; + ct = 1; + for ct1 = 1:n + for ct2 = 1:m + Names(ct,1) = sprintf("[%d,%d]",ct2,ct1); + ct = ct+1; + end + end + end + + end +end + diff --git a/ChannelBPSK.slx b/ChannelBPSK.slx new file mode 100644 index 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b/dc2bi.m new file mode 100644 index 0000000..fa4366f --- /dev/null +++ b/dc2bi.m @@ -0,0 +1,9 @@ +function vecargout = dc2bi(intgargin) +%UNTITLED Summary of this function goes here +% Detailed explanation goes here +biNum = dec2bin(intgargin); + emptyVec = zeros(4,1); + + + +end \ No newline at end of file diff --git a/ddc2bi.m b/ddc2bi.m new file mode 100644 index 0000000..fa4366f --- /dev/null +++ b/ddc2bi.m @@ -0,0 +1,9 @@ +function vecargout = dc2bi(intgargin) +%UNTITLED Summary of this function goes here +% Detailed explanation goes here +biNum = dec2bin(intgargin); + emptyVec = zeros(4,1); + + + +end \ No newline at end of file diff --git a/deconvert.mlx b/deconvert.mlx new file mode 100644 index 0000000000000000000000000000000000000000..b558f8a6cf35591330b8aeff70e3b9de8361b565 GIT binary patch literal 2926 zcmaKu2{=^y8^_1K4>6ahFj-Og1Of>FZ_XO{`ruJMct`6Cekhy+EXW&8O6WY%q{w%f8p_#mn)t|1mtATuLhKrs zVWHNO33OUvocBFIB%X3zPdl{YYFC0x|EDb<;pRNh9 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java/lang/invoke/CallSite THROW_UCS Ljava/lang/invoke/MethodHandle; java/lang/invoke/MethodHandleImpl$AsVarargsCollector +staticfield java/lang/invoke/CallSite TARGET_OFFSET J 12 +ciInstanceKlass java/lang/invoke/ConstantCallSite 1 1 42 10 9 10 100 10 9 100 10 10 7 7 1 1 1 1 1 1 1 1 100 1 1 1 1 1 1 1 12 12 12 1 12 12 1 12 1 1 1 1 1 1 +ciInstanceKlass java/lang/invoke/MutableCallSite 0 0 57 10 10 9 10 10 10 9 10 10 100 10 100 100 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 12 12 12 12 12 12 12 12 100 12 1 12 1 1 1 1 1 1 1 1 1 1 1 1 1 +ciInstanceKlass java/lang/invoke/VolatileCallSite 0 0 33 10 10 10 10 10 10 100 100 1 1 1 1 1 1 1 1 1 1 1 12 12 12 12 12 12 1 1 1 1 1 1 1 +instanceKlass java/lang/StringBuilder +instanceKlass java/lang/StringBuffer +ciInstanceKlass java/lang/AbstractStringBuilder 1 1 318 7 10 9 9 10 10 10 7 3 10 3 100 10 100 10 10 10 10 100 10 10 10 8 10 10 10 10 10 10 10 10 10 10 10 7 10 11 10 8 100 10 8 10 10 8 8 10 10 11 3 8 10 10 7 5 0 8 10 10 10 10 10 10 10 10 100 10 8 8 10 10 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sun/misc/Unsafe ARRAY_DOUBLE_BASE_OFFSET I 16 +staticfield sun/misc/Unsafe ARRAY_OBJECT_BASE_OFFSET I 16 +staticfield sun/misc/Unsafe ARRAY_BOOLEAN_INDEX_SCALE I 1 +staticfield sun/misc/Unsafe ARRAY_BYTE_INDEX_SCALE I 1 +staticfield sun/misc/Unsafe ARRAY_SHORT_INDEX_SCALE I 2 +staticfield sun/misc/Unsafe ARRAY_CHAR_INDEX_SCALE I 2 +staticfield sun/misc/Unsafe ARRAY_INT_INDEX_SCALE I 4 +staticfield sun/misc/Unsafe ARRAY_LONG_INDEX_SCALE I 8 +staticfield sun/misc/Unsafe ARRAY_FLOAT_INDEX_SCALE I 4 +staticfield sun/misc/Unsafe ARRAY_DOUBLE_INDEX_SCALE I 8 +staticfield sun/misc/Unsafe ARRAY_OBJECT_INDEX_SCALE I 4 +staticfield sun/misc/Unsafe ADDRESS_SIZE I 8 +instanceKlass sun/nio/ch/ChannelInputStream +instanceKlass sun/net/www/http/ChunkedInputStream +instanceKlass com/sun/imageio/plugins/common/InputStreamAdapter +instanceKlass org/apache/http/nio/entity/ContentInputStream +instanceKlass sun/security/ssl/ByteBufferInputStream +instanceKlass sun/security/ssl/HandshakeInStream 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index 0000000..c6b694a --- /dev/null +++ b/resetMap.m @@ -0,0 +1,17 @@ +function in = resetMap(in,obsMat) +% Reset function for multi agent area coverage example + +% Copyright 2020 The MathWorks, Inc. + + gridSize = [12 12]; + isvalid = false; + while ~isvalid + rows = randperm(gridSize(1),3); + cols = randperm(gridSize(2),3); + s0 = [rows' cols']; + if all(~all(s0(1,:) == obsMat,2)) && all(~all(s0(2,:) == obsMat,2)) && all(~all(s0(3,:) == obsMat,2)) + isvalid = true; + end + end + in = setVariable(in, 's0', s0); +end \ No newline at end of file diff --git a/rlAreaCoverageAgents.mat b/rlAreaCoverageAgents.mat new file mode 100644 index 0000000000000000000000000000000000000000..209003d017c5b9f4046f8e238bb36cae0ac8868f GIT binary patch literal 3378166 zcmbSyWl&vB&}MLV2=4Cg?he7-g1fs*fFK9ORZ?3;Qi_6?je|l}Qk&Jr-pQJU;)|1omyN53vk=7>X+1?XJ{}ed zX%A})FKa6bR~I1)Z98uYB?}h{3O))>J|Rv{A#N@TE)Fg(ivPz}3H9lJHz-9_jDMEl zKk>^yurxQ%h8l5_n1LFJK*aAruKLq6cHt>6cMY8Qp8q`e73Ng1Dpg^06lpptt}Qm1 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newline at end of file diff --git a/GridWorld.asv b/GridWorld.asv new file mode 100644 index 0000000..75f78ee --- /dev/null +++ b/GridWorld.asv @@ -0,0 +1,501 @@ +classdef GridWorld < matlab.System +% GridWorld represents a 12x12 deterministic grid world with 3 robots. + +% Copyright 2020-2022 The MathWorks, Inc. + + % Public, tunable properties + properties + % Initial position of robots + InitialStates (3,2) double = [2 2; 11 4; 3 12] + end + + % Public, non-tunable properties + properties(Nontunable) + % Obstacle matrix + Obstacles double = -1 + % Max step count + MaxStepCount (1,1) double = 500 + end + + properties(DiscreteState) + % Discretized XY space with cells containing 0.5 or 1.0 + % 0: unexplored + % 0.25: explored by robot A + % 0.50: explored by robot B + % 0.75: explored by robot B + % 1.0: obstacle + Grid + % States of robot A,B: [rowA colA; rowB colB] + States + % Step count + StepCount + % Individual cell exploration count + NumExploredCells + end + + % Pre-computed constants + properties(Access = private) + % Handle to figure + Figure + % Grid size [numrows numcols] + Size (1,2) double = [12 12] + end + + methods + % Constructor + function this = GridWorld(varargin) + % Support name-value pair arguments when constructing object + setProperties(this,nargin,varargin{:}) + end + end + + methods(Access = protected) + %% Common functions + function setupImpl(obj) %#ok + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + % Implement algorithm. Calculate y as a function of input u and + % discrete states. + + numRobots = 3; + + % Rewards are: + % Agent moves to unexplored cell: +20 + % Agent moves to explored cell: 0 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) +% case 0 +% % Wait +% next_states(idx,:) = state; +% rewards(idx) = rewards(idx) - 10; % lazy penalty + case 1 + % Move up + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move left + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move right + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 5 + % Move right-up NorthEast + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 6 + % Move Left up NorthWest + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 7 + % Move Right Down South East + if state(1) > 1 && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 8 + % Move Left Down South West + if state(1) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + end + end + + % update grid and reward agents for new exploration + for idx = 1:numRobots + r = next_states(idx,1); + c = next_states(idx,2); + if obj.Grid(r,c) == 0.0 + % robot explores an unexplored cell + rewards(idx) = rewards(idx) + 20; + % update grid values + switch(idx) + case 1 + obj.Grid(r,c) = 0.25; % explored by A + obj.NumExploredCells = obj.NumExploredCells + [1 0 0]; + case 2 + obj.Grid(r,c) = 0.5; % explored by B + obj.NumExploredCells = obj.NumExploredCells + [0 1 0]; + case 3 + obj.Grid(r,c) = 0.75; % explored by C + obj.NumExploredCells = obj.NumExploredCells + [0 0 1]; + end + end + end + + % coverage metrics + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + if totalExploredCells >= totalCells + isdone = 1; + rewards = rewards + 4000 * (totalExploredCells'/totalCells); + end + + % Observation for each agent is a 12x12 4-channel image. The + % channels are: + % 1. Obstacle channel - cells with obstacles are 1, rest 0 + % 2. Self channel - cell with the agent's state is 1, rest 0 + % 3. Friend channel - cell with other agent's state is 1, rest 0 + % 4. Coverage channel - cells that are unexplored are 1, rest 0 + observations = zeros(obj.Size(1),obj.Size(2),4,numRobots); + for idx = 1:numRobots + obstacleChannel = 1.0 * (obj.Grid == 1.0); + + selfIdx = idx; + selfRow = next_states(selfIdx,1); + selfCol = next_states(selfIdx,2); + selfChannel = zeros(obj.Size); + selfChannel(selfRow,selfCol) = 1.0; + + friendIdxs = idx ~= (1:numRobots); + friendRows = next_states(friendIdxs,1); + friendCols = next_states(friendIdxs,2); + friendChannel = zeros(obj.Size); + friendChannel(friendRows(1),friendCols(1)) = 1.0; + friendChannel(friendRows(2),friendCols(2)) = 1.0; + + coverageChannel = 1.0 * (obj.Grid == 0); + + observations(:,:,1,idx) = obstacleChannel; + observations(:,:,2,idx) = selfChannel; + observations(:,:,3,idx) = friendChannel; + observations(:,:,4,idx) = coverageChannel; + end + + % Scale down rewards + rewards = rewards./20; + + % DEBUG + if all(next_states(1,:)==next_states(2,:)) || ... + all(next_states(2,:)==next_states(3,:)) || ... + all(next_states(1,:)==next_states(3,:)) + fprintf('Assertion: Invalid state.\n'); + end + + % Update states + obj.States = next_states; + obj.StepCount = obj.StepCount + 1; + + % plot the environment + if obj.StepCount <= obj.MaxStepCount + plot(obj); + end + + end + + function resetImpl(obj) + % Initialize / reset discrete-state properties + + % set unexplored cells + obj.Grid = zeros(obj.Size); + + % set obstacle cells + if ~isequal(obj.Obstacles,-1) + for idx = 1:size(obj.Obstacles,1) + r = obj.Obstacles(idx,1); + c = obj.Obstacles(idx,2); + obj.Grid(r,c) = 1.0; + end + end + + % set step count + obj.StepCount = 0; + + % explored cells + obj.NumExploredCells = ones(1,3); + + % set robot cells + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + obj.Grid(sA(1),sA(2)) = 0.25; + obj.Grid(sB(1),sB(2)) = 0.50; + obj.Grid(sC(1),sC(2)) = 0.75; + obj.States = obj.InitialStates; + end + + %% Backup/restore functions + function s = saveObjectImpl(obj) + % Set properties in structure s to values in object obj + + % Set public properties and states + s = saveObjectImpl@matlab.System(obj); + + % Set private and protected properties + %s.myproperty = obj.myproperty; + end + + function loadObjectImpl(obj,s,wasLocked) + % Set properties in object obj to values in structure s + + % Set private and protected properties + % obj.myproperty = s.myproperty; + + % Set public properties and states + loadObjectImpl@matlab.System(obj,s,wasLocked); + end + + %% Simulink functions + function ds = getDiscreteStateImpl(obj) + % Return structure of properties with DiscreteState attribute + ds.Grid = obj.Grid; + ds.States = obj.States; + ds.StepCount = obj.StepCount; + ds.NumExploredCells = obj.NumExploredCells; + end + + function flag = isInputSizeMutableImpl(obj,index) %#ok + % Return false if input size cannot change + % between calls to the System object + flag = false; + end + + function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok + % Return size for each output port + out1 = [12 12 4 3]; % observation + out2 = [3 1]; % reward + out3 = [1 1]; % isdone + end + + function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok + % Return data type for each output port + out1 = "double"; + out2 = "double"; + out3 = "double"; + end + + function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok + % Return true for each output port with complex data + out1 = false; + out2 = false; + out3 = false; + end + + function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok + % Return true for each output port with fixed size + out1 = true; + out2 = true; + out3 = true; + end + + function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name) + % Return size, data type, and complexity of discrete-state + % specified in name + if strcmpi(name,'Grid') + sz = obj.Size; + dt = "double"; + cp = false; + elseif strcmpi(name,'States') + sz = [3 2]; + dt = "double"; + cp = false; + elseif strcmpi(name,'StepCount') + sz = [1 1]; + dt = "double"; + cp = false; + elseif strcmpi(name,'NumExploredCells') + sz = [1 3]; + dt = "double"; + cp = false; + else + error(['Error: Incorrect State Name: ', name.']); + end + end + + function icon = getIconImpl(obj) %#ok + % Define icon for System block + icon = mfilename("class"); % Use class name + end + end + + methods(Static, Access = protected) + %% Simulink customization functions + function header = getHeaderImpl + % Define header panel for System block dialog + header = matlab.system.display.Header(mfilename("class")); + end + + function group = getPropertyGroupsImpl + % Define property section(s) for System block dialog + group = matlab.system.display.Section(mfilename("class")); + end + + end + + methods(Access=private) + function collision = checkCollision(obj,new_state,other_states) + % Create array of occupied states + if isequal(obj.Obstacles,-1) + occupiedStates = other_states; + else + occupiedStates = [other_states; obj.Obstacles]; + end + % check collision + collision = any(all(new_state==occupiedStates,2)); + end + + function plot(obj) + persistent ax cells robots + + if isempty(ax) || ~isvalid(ax) + % build figure + f = figure; + f.Position = [195 120 400 300]; + %f.Visible = 'on'; % force external figure + ax = gca(f); + hold(ax,'on'); + if ~isequal(obj.Obstacles,-1) + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + else + cmap = [255 255 255;... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + ]./255; % black (obstacles) + end + colormap(ax,cmap); + + % plot cells + cdata = obj.Grid; + cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata); + + % plot grid lines + x = 0:1:obj.Size(2); + y = 0:1:obj.Size(1); + [X,Y] = meshgrid(x,y); + plot(ax,X,Y,'Color',[0.94 0.94 0.94]); + plot(ax,Y,X,'Color',[0.94 0.94 0.94]); + + % plot robots + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + robots = gobjects(1,2); + robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1); + robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1); + robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1); + + % time text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage)); + + ax.XTick = 0:1:obj.Size(1); + ax.YTick = 0:1:obj.Size(2); + ax.XTickLabel = {}; + ax.YTickLabel = {}; + axis(ax,'equal'); + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + ax.Box = 'on'; + end + + % update color map + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + if all(obj.Grid~=0,'all') + cmap = cmap(2:end,:); % no unexplored cells + end + if isequal(obj.Obstacles,-1) + cmap = cmap(1:end-1,:); % no obstacles + end + colormap(ax,cmap); + + % update cell colors + cdata = obj.Grid; + cells.CData = cdata; + + % update robot positions + for idx = 1:3 + s = obj.States(idx,:); + robots(idx).Position = [s(2)-1 s(1)-1 1 1]; + end + + % update info text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage); + + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + grid(ax,'on'); + + drawnow(); + end + end +end diff --git a/GridWorld.m b/GridWorld.m new file mode 100644 index 0000000..7f5d517 --- /dev/null +++ b/GridWorld.m @@ -0,0 +1,501 @@ +classdef GridWorld < matlab.System +% GridWorld represents a 12x12 deterministic grid world with 3 robots. + +% Copyright 2020-2022 The MathWorks, Inc. + + % Public, tunable properties + properties + % Initial position of robots + InitialStates (3,2) double = [2 2; 11 4; 3 12] + end + + % Public, non-tunable properties + properties(Nontunable) + % Obstacle matrix + Obstacles double = -1 + % Max step count + MaxStepCount (1,1) double = 500 + end + + properties(DiscreteState) + % Discretized XY space with cells containing 0.5 or 1.0 + % 0: unexplored + % 0.25: explored by robot A + % 0.50: explored by robot B + % 0.75: explored by robot B + % 1.0: obstacle + Grid + % States of robot A,B: [rowA colA; rowB colB] + States + % Step count + StepCount + % Individual cell exploration count + NumExploredCells + end + + % Pre-computed constants + properties(Access = private) + % Handle to figure + Figure + % Grid size [numrows numcols] + Size (1,2) double = [12 12] + end + + methods + % Constructor + function this = GridWorld(varargin) + % Support name-value pair arguments when constructing object + setProperties(this,nargin,varargin{:}) + end + end + + methods(Access = protected) + %% Common functions + function setupImpl(obj) %#ok + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + % Implement algorithm. Calculate y as a function of input u and + % discrete states. + + numRobots = 3; + + % Rewards are: + % Agent moves to unexplored cell: +20 + % Agent moves to explored cell: 0 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) +% case 0 +% % Wait +% next_states(idx,:) = state; +% rewards(idx) = rewards(idx) - 10; % lazy penalty + case 1 + % Move up + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move left + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move right + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 5 + % Move right-up NorthEast + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right-up NorthEast + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 6 + % Move Left up NorthWest + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go Left up NorthWest + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 7 + % Move Right Down South East + if state(1) > 1 && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) && state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go Right Down South East + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 8 + % Move Left Down South West + if state(1) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) && state(2) > 1 && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go Left Down South West + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + end + end + + % update grid and reward agents for new exploration + for idx = 1:numRobots + r = next_states(idx,1); + c = next_states(idx,2); + if obj.Grid(r,c) == 0.0 + % robot explores an unexplored cell + rewards(idx) = rewards(idx) + 20; + % update grid values + switch(idx) + case 1 + obj.Grid(r,c) = 0.25; % explored by A + obj.NumExploredCells = obj.NumExploredCells + [1 0 0]; + case 2 + obj.Grid(r,c) = 0.5; % explored by B + obj.NumExploredCells = obj.NumExploredCells + [0 1 0]; + case 3 + obj.Grid(r,c) = 0.75; % explored by C + obj.NumExploredCells = obj.NumExploredCells + [0 0 1]; + end + end + end + + % coverage metrics + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + if totalExploredCells >= totalCells + isdone = 1; + rewards = rewards + 4000 * (totalExploredCells'/totalCells); + end + + % Observation for each agent is a 12x12 4-channel image. The + % channels are: + % 1. Obstacle channel - cells with obstacles are 1, rest 0 + % 2. Self channel - cell with the agent's state is 1, rest 0 + % 3. Friend channel - cell with other agent's state is 1, rest 0 + % 4. Coverage channel - cells that are unexplored are 1, rest 0 + observations = zeros(obj.Size(1),obj.Size(2),4,numRobots); + for idx = 1:numRobots + obstacleChannel = 1.0 * (obj.Grid == 1.0); + + selfIdx = idx; + selfRow = next_states(selfIdx,1); + selfCol = next_states(selfIdx,2); + selfChannel = zeros(obj.Size); + selfChannel(selfRow,selfCol) = 1.0; + + friendIdxs = idx ~= (1:numRobots); + friendRows = next_states(friendIdxs,1); + friendCols = next_states(friendIdxs,2); + friendChannel = zeros(obj.Size); + friendChannel(friendRows(1),friendCols(1)) = 1.0; + friendChannel(friendRows(2),friendCols(2)) = 1.0; + + coverageChannel = 1.0 * (obj.Grid == 0); + + observations(:,:,1,idx) = obstacleChannel; + observations(:,:,2,idx) = selfChannel; + observations(:,:,3,idx) = friendChannel; + observations(:,:,4,idx) = coverageChannel; + end + + % Scale down rewards + rewards = rewards./20; + + % DEBUG + if all(next_states(1,:)==next_states(2,:)) || ... + all(next_states(2,:)==next_states(3,:)) || ... + all(next_states(1,:)==next_states(3,:)) + fprintf('Assertion: Invalid state.\n'); + end + + % Update states + obj.States = next_states; + obj.StepCount = obj.StepCount + 1; + + % plot the environment + if obj.StepCount <= obj.MaxStepCount + plot(obj); + end + + end + + function resetImpl(obj) + % Initialize / reset discrete-state properties + + % set unexplored cells + obj.Grid = zeros(obj.Size); + + % set obstacle cells + if ~isequal(obj.Obstacles,-1) + for idx = 1:size(obj.Obstacles,1) + r = obj.Obstacles(idx,1); + c = obj.Obstacles(idx,2); + obj.Grid(r,c) = 1.0; + end + end + + % set step count + obj.StepCount = 0; + + % explored cells + obj.NumExploredCells = ones(1,3); + + % set robot cells + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + obj.Grid(sA(1),sA(2)) = 0.25; + obj.Grid(sB(1),sB(2)) = 0.50; + obj.Grid(sC(1),sC(2)) = 0.75; + obj.States = obj.InitialStates; + end + + %% Backup/restore functions + function s = saveObjectImpl(obj) + % Set properties in structure s to values in object obj + + % Set public properties and states + s = saveObjectImpl@matlab.System(obj); + + % Set private and protected properties + %s.myproperty = obj.myproperty; + end + + function loadObjectImpl(obj,s,wasLocked) + % Set properties in object obj to values in structure s + + % Set private and protected properties + % obj.myproperty = s.myproperty; + + % Set public properties and states + loadObjectImpl@matlab.System(obj,s,wasLocked); + end + + %% Simulink functions + function ds = getDiscreteStateImpl(obj) + % Return structure of properties with DiscreteState attribute + ds.Grid = obj.Grid; + ds.States = obj.States; + ds.StepCount = obj.StepCount; + ds.NumExploredCells = obj.NumExploredCells; + end + + function flag = isInputSizeMutableImpl(obj,index) %#ok + % Return false if input size cannot change + % between calls to the System object + flag = false; + end + + function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok + % Return size for each output port + out1 = [12 12 4 3]; % observation + out2 = [3 1]; % reward + out3 = [1 1]; % isdone + end + + function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok + % Return data type for each output port + out1 = "double"; + out2 = "double"; + out3 = "double"; + end + + function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok + % Return true for each output port with complex data + out1 = false; + out2 = false; + out3 = false; + end + + function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok + % Return true for each output port with fixed size + out1 = true; + out2 = true; + out3 = true; + end + + function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name) + % Return size, data type, and complexity of discrete-state + % specified in name + if strcmpi(name,'Grid') + sz = obj.Size; + dt = "double"; + cp = false; + elseif strcmpi(name,'States') + sz = [3 2]; + dt = "double"; + cp = false; + elseif strcmpi(name,'StepCount') + sz = [1 1]; + dt = "double"; + cp = false; + elseif strcmpi(name,'NumExploredCells') + sz = [1 3]; + dt = "double"; + cp = false; + else + error(['Error: Incorrect State Name: ', name.']); + end + end + + function icon = getIconImpl(obj) %#ok + % Define icon for System block + icon = mfilename("class"); % Use class name + end + end + + methods(Static, Access = protected) + %% Simulink customization functions + function header = getHeaderImpl + % Define header panel for System block dialog + header = matlab.system.display.Header(mfilename("class")); + end + + function group = getPropertyGroupsImpl + % Define property section(s) for System block dialog + group = matlab.system.display.Section(mfilename("class")); + end + + end + + methods(Access=private) + function collision = checkCollision(obj,new_state,other_states) + % Create array of occupied states + if isequal(obj.Obstacles,-1) + occupiedStates = other_states; + else + occupiedStates = [other_states; obj.Obstacles]; + end + % check collision + collision = any(all(new_state==occupiedStates,2)); + end + + function plot(obj) + persistent ax cells robots + + if isempty(ax) || ~isvalid(ax) + % build figure + f = figure; + f.Position = [195 120 400 300]; + %f.Visible = 'on'; % force external figure + ax = gca(f); + hold(ax,'on'); + if ~isequal(obj.Obstacles,-1) + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + else + cmap = [255 255 255;... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + ]./255; % black (obstacles) + end + colormap(ax,cmap); + + % plot cells + cdata = obj.Grid; + cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata); + + % plot grid lines + x = 0:1:obj.Size(2); + y = 0:1:obj.Size(1); + [X,Y] = meshgrid(x,y); + plot(ax,X,Y,'Color',[0.94 0.94 0.94]); + plot(ax,Y,X,'Color',[0.94 0.94 0.94]); + + % plot robots + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + robots = gobjects(1,2); + robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1); + robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1); + robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1); + + % time text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage)); + + ax.XTick = 0:1:obj.Size(1); + ax.YTick = 0:1:obj.Size(2); + ax.XTickLabel = {}; + ax.YTickLabel = {}; + axis(ax,'equal'); + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + ax.Box = 'on'; + end + + % update color map + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + if all(obj.Grid~=0,'all') + cmap = cmap(2:end,:); % no unexplored cells + end + if isequal(obj.Obstacles,-1) + cmap = cmap(1:end-1,:); % no obstacles + end + colormap(ax,cmap); + + % update cell colors + cdata = obj.Grid; + cells.CData = cdata; + + % update robot positions + for idx = 1:3 + s = obj.States(idx,:); + robots(idx).Position = [s(2)-1 s(1)-1 1 1]; + end + + % update info text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage); + + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + grid(ax,'on'); + + drawnow(); + end + end +end diff --git a/GridWorldV0.m b/GridWorldV0.m new file mode 100644 index 0000000..02807fe --- /dev/null +++ b/GridWorldV0.m @@ -0,0 +1,462 @@ +classdef GridWorld < matlab.System +% GridWorld represents a 12x12 deterministic grid world with 3 robots. + +% Copyright 2020-2022 The MathWorks, Inc. + + % Public, tunable properties + properties + % Initial position of robots + InitialStates (3,2) double = [2 2; 11 4; 3 12] + end + + % Public, non-tunable properties + properties(Nontunable) + % Obstacle matrix + Obstacles double = -1 + % Max step count + MaxStepCount (1,1) double = 500 + end + + properties(DiscreteState) + % Discretized XY space with cells containing 0.5 or 1.0 + % 0: unexplored + % 0.25: explored by robot A + % 0.50: explored by robot B + % 0.75: explored by robot B + % 1.0: obstacle + Grid + % States of robot A,B: [rowA colA; rowB colB] + States + % Step count + StepCount + % Individual cell exploration count + NumExploredCells + end + + % Pre-computed constants + properties(Access = private) + % Handle to figure + Figure + % Grid size [numrows numcols] + Size (1,2) double = [12 12] + end + + methods + % Constructor + function this = GridWorld(varargin) + % Support name-value pair arguments when constructing object + setProperties(this,nargin,varargin{:}) + end + end + + methods(Access = protected) + %% Common functions + function setupImpl(obj) %#ok + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + % Implement algorithm. Calculate y as a function of input u and + % discrete states. + + numRobots = 3; + + % Rewards are: + % Agent moves to unexplored cell: +20 + % Agent moves to explored cell: 0 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) + case 0 + % Wait + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; % lazy penalty + case 1 + % Move up + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move left + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move right + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + + end + end + + % update grid and reward agents for new exploration + for idx = 1:numRobots + r = next_states(idx,1); + c = next_states(idx,2); + if obj.Grid(r,c) == 0.0 + % robot explores an unexplored cell + rewards(idx) = rewards(idx) + 20; + % update grid values + switch(idx) + case 1 + obj.Grid(r,c) = 0.25; % explored by A + obj.NumExploredCells = obj.NumExploredCells + [1 0 0]; + case 2 + obj.Grid(r,c) = 0.5; % explored by B + obj.NumExploredCells = obj.NumExploredCells + [0 1 0]; + case 3 + obj.Grid(r,c) = 0.75; % explored by C + obj.NumExploredCells = obj.NumExploredCells + [0 0 1]; + end + end + end + + % coverage metrics + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + if totalExploredCells >= totalCells + isdone = 1; + rewards = rewards + 4000 * (totalExploredCells'/totalCells); + end + + % Observation for each agent is a 12x12 4-channel image. The + % channels are: + % 1. Obstacle channel - cells with obstacles are 1, rest 0 + % 2. Self channel - cell with the agent's state is 1, rest 0 + % 3. Friend channel - cell with other agent's state is 1, rest 0 + % 4. Coverage channel - cells that are unexplored are 1, rest 0 + observations = zeros(obj.Size(1),obj.Size(2),4,numRobots); + for idx = 1:numRobots + obstacleChannel = 1.0 * (obj.Grid == 1.0); + + selfIdx = idx; + selfRow = next_states(selfIdx,1); + selfCol = next_states(selfIdx,2); + selfChannel = zeros(obj.Size); + selfChannel(selfRow,selfCol) = 1.0; + + friendIdxs = idx ~= (1:numRobots); + friendRows = next_states(friendIdxs,1); + friendCols = next_states(friendIdxs,2); + friendChannel = zeros(obj.Size); + friendChannel(friendRows(1),friendCols(1)) = 1.0; + friendChannel(friendRows(2),friendCols(2)) = 1.0; + + coverageChannel = 1.0 * (obj.Grid == 0); + + observations(:,:,1,idx) = obstacleChannel; + observations(:,:,2,idx) = selfChannel; + observations(:,:,3,idx) = friendChannel; + observations(:,:,4,idx) = coverageChannel; + end + + % Scale down rewards + rewards = rewards./20; + + % DEBUG + if all(next_states(1,:)==next_states(2,:)) || ... + all(next_states(2,:)==next_states(3,:)) || ... + all(next_states(1,:)==next_states(3,:)) + fprintf('Assertion: Invalid state.\n'); + end + + % Update states + obj.States = next_states; + obj.StepCount = obj.StepCount + 1; + + % plot the environment + if obj.StepCount <= obj.MaxStepCount + plot(obj); + end + + end + + function resetImpl(obj) + % Initialize / reset discrete-state properties + + % set unexplored cells + obj.Grid = zeros(obj.Size); + + % set obstacle cells + if ~isequal(obj.Obstacles,-1) + for idx = 1:size(obj.Obstacles,1) + r = obj.Obstacles(idx,1); + c = obj.Obstacles(idx,2); + obj.Grid(r,c) = 1.0; + end + end + + % set step count + obj.StepCount = 0; + + % explored cells + obj.NumExploredCells = ones(1,3); + + % set robot cells + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + obj.Grid(sA(1),sA(2)) = 0.25; + obj.Grid(sB(1),sB(2)) = 0.50; + obj.Grid(sC(1),sC(2)) = 0.75; + obj.States = obj.InitialStates; + end + + %% Backup/restore functions + function s = saveObjectImpl(obj) + % Set properties in structure s to values in object obj + + % Set public properties and states + s = saveObjectImpl@matlab.System(obj); + + % Set private and protected properties + %s.myproperty = obj.myproperty; + end + + function loadObjectImpl(obj,s,wasLocked) + % Set properties in object obj to values in structure s + + % Set private and protected properties + % obj.myproperty = s.myproperty; + + % Set public properties and states + loadObjectImpl@matlab.System(obj,s,wasLocked); + end + + %% Simulink functions + function ds = getDiscreteStateImpl(obj) + % Return structure of properties with DiscreteState attribute + ds.Grid = obj.Grid; + ds.States = obj.States; + ds.StepCount = obj.StepCount; + ds.NumExploredCells = obj.NumExploredCells; + end + + function flag = isInputSizeMutableImpl(obj,index) %#ok + % Return false if input size cannot change + % between calls to the System object + flag = false; + end + + function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok + % Return size for each output port + out1 = [12 12 4 3]; % observation + out2 = [3 1]; % reward + out3 = [1 1]; % isdone + end + + function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok + % Return data type for each output port + out1 = "double"; + out2 = "double"; + out3 = "double"; + end + + function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok + % Return true for each output port with complex data + out1 = false; + out2 = false; + out3 = false; + end + + function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok + % Return true for each output port with fixed size + out1 = true; + out2 = true; + out3 = true; + end + + function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name) + % Return size, data type, and complexity of discrete-state + % specified in name + if strcmpi(name,'Grid') + sz = obj.Size; + dt = "double"; + cp = false; + elseif strcmpi(name,'States') + sz = [3 2]; + dt = "double"; + cp = false; + elseif strcmpi(name,'StepCount') + sz = [1 1]; + dt = "double"; + cp = false; + elseif strcmpi(name,'NumExploredCells') + sz = [1 3]; + dt = "double"; + cp = false; + else + error(['Error: Incorrect State Name: ', name.']); + end + end + + function icon = getIconImpl(obj) %#ok + % Define icon for System block + icon = mfilename("class"); % Use class name + end + end + + methods(Static, Access = protected) + %% Simulink customization functions + function header = getHeaderImpl + % Define header panel for System block dialog + header = matlab.system.display.Header(mfilename("class")); + end + + function group = getPropertyGroupsImpl + % Define property section(s) for System block dialog + group = matlab.system.display.Section(mfilename("class")); + end + + end + + methods(Access=private) + function collision = checkCollision(obj,new_state,other_states) + % Create array of occupied states + if isequal(obj.Obstacles,-1) + occupiedStates = other_states; + else + occupiedStates = [other_states; obj.Obstacles]; + end + % check collision + collision = any(all(new_state==occupiedStates,2)); + end + + function plot(obj) + persistent ax cells robots + + if isempty(ax) || ~isvalid(ax) + % build figure + f = figure; + f.Position = [195 120 400 300]; + %f.Visible = 'on'; % force external figure + ax = gca(f); + hold(ax,'on'); + if ~isequal(obj.Obstacles,-1) + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + else + cmap = [255 255 255;... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + ]./255; % black (obstacles) + end + colormap(ax,cmap); + + % plot cells + cdata = obj.Grid; + cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata); + + % plot grid lines + x = 0:1:obj.Size(2); + y = 0:1:obj.Size(1); + [X,Y] = meshgrid(x,y); + plot(ax,X,Y,'Color',[0.94 0.94 0.94]); + plot(ax,Y,X,'Color',[0.94 0.94 0.94]); + + % plot robots + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + robots = gobjects(1,2); + robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1); + robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1); + robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1); + + % time text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage)); + + ax.XTick = 0:1:obj.Size(1); + ax.YTick = 0:1:obj.Size(2); + ax.XTickLabel = {}; + ax.YTickLabel = {}; + axis(ax,'equal'); + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + ax.Box = 'on'; + end + + % update color map + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + if all(obj.Grid~=0,'all') + cmap = cmap(2:end,:); % no unexplored cells + end + if isequal(obj.Obstacles,-1) + cmap = cmap(1:end-1,:); % no obstacles + end + colormap(ax,cmap); + + % update cell colors + cdata = obj.Grid; + cells.CData = cdata; + + % update robot positions + for idx = 1:3 + s = obj.States(idx,:); + robots(idx).Position = [s(2)-1 s(1)-1 1 1]; + end + + % update info text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage); + + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + grid(ax,'on'); + + drawnow(); + end + end +end diff --git a/GridWorldV1.m b/GridWorldV1.m new file mode 100644 index 0000000..1b10d5b --- /dev/null +++ b/GridWorldV1.m @@ -0,0 +1,504 @@ +classdef GridWorld < matlab.System +% GridWorld represents a 12x12 deterministic grid world with 3 robots. + +% Copyright 2020-2022 The MathWorks, Inc. + + % Public, tunable properties + properties + % Initial position of robots + InitialStates (3,2) double = [2 2; 11 4; 3 12] + end + + % Public, non-tunable properties + properties(Nontunable) + % Obstacle matrix + Obstacles double = -1 + % Max step count + MaxStepCount (1,1) double = 500 + end + + properties(DiscreteState) + % Discretized XY space with cells containing 0.5 or 1.0 + % 0: unexplored + % 0.25: explored by robot A + % 0.50: explored by robot B + % 0.75: explored by robot B + % 1.0: obstacle + Grid + % States of robot A,B: [rowA colA; rowB colB] + States + % Step count + StepCount + % Individual cell exploration count + NumExploredCells + end + + % Pre-computed constants + properties(Access = private) + % Handle to figure + Figure + % Grid size [numrows numcols] + Size (1,2) double = [64 64] + end + + methods + % Constructor + function this = GridWorld(varargin) + % Support name-value pair arguments when constructing object + setProperties(this,nargin,varargin{:}) + end + end + + methods(Access = protected) + %% Common functions + function setupImpl(obj) %#ok + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + % Implement algorithm. Calculate y as a function of input u and + % discrete states. + +% numRobots = 3; + numRobots = 1; + + % Rewards are: + % Agent moves to unexplored cell: +20 + % Agent moves to explored cell: 0 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) + case 0 + % Wait + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; % lazy penalty + case 1 + % Move up + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move left + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move right + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 5 + % Move right-up NorthEast + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + + case 6 + % Move Left up NorthWest + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 7 + % Move Right Down South East + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 8 + % Move Left Down South West + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + end + end + + % update grid and reward agents for new exploration + for idx = 1:numRobots + r = next_states(idx,1); + c = next_states(idx,2); + if obj.Grid(r,c) == 0.0 + % robot explores an unexplored cell + rewards(idx) = rewards(idx) + 20; + % update grid values + switch(idx) + case 1 + obj.Grid(r,c) = 0.25; % explored by A + obj.NumExploredCells = obj.NumExploredCells + [1 0 0]; + case 2 + obj.Grid(r,c) = 0.5; % explored by B + obj.NumExploredCells = obj.NumExploredCells + [0 1 0]; + case 3 + obj.Grid(r,c) = 0.75; % explored by C + obj.NumExploredCells = obj.NumExploredCells + [0 0 1]; + end + end + end + + % coverage metrics + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + if totalExploredCells >= totalCells + isdone = 1; + rewards = rewards + 4000 * (totalExploredCells'/totalCells); + end + + % Observation for each agent is a 12x12 4-channel image. The + % channels are: + % 1. Obstacle channel - cells with obstacles are 1, rest 0 + % 2. Self channel - cell with the agent's state is 1, rest 0 + % 3. Friend channel - cell with other agent's state is 1, rest 0 + % 4. Coverage channel - cells that are unexplored are 1, rest 0 + observations = zeros(obj.Size(1),obj.Size(2),4,numRobots); + for idx = 1:numRobots + obstacleChannel = 1.0 * (obj.Grid == 1.0); + + selfIdx = idx; + selfRow = next_states(selfIdx,1); + selfCol = next_states(selfIdx,2); + selfChannel = zeros(obj.Size); + selfChannel(selfRow,selfCol) = 1.0; + + friendIdxs = idx ~= (1:numRobots); + friendRows = next_states(friendIdxs,1); + friendCols = next_states(friendIdxs,2); + friendChannel = zeros(obj.Size); + friendChannel(friendRows(1),friendCols(1)) = 1.0; + friendChannel(friendRows(2),friendCols(2)) = 1.0; + + coverageChannel = 1.0 * (obj.Grid == 0); + + observations(:,:,1,idx) = obstacleChannel; + observations(:,:,2,idx) = selfChannel; + observations(:,:,3,idx) = friendChannel; + observations(:,:,4,idx) = coverageChannel; + end + + % Scale down rewards + rewards = rewards./20; + + % DEBUG + if all(next_states(1,:)==next_states(2,:)) || ... + all(next_states(2,:)==next_states(3,:)) || ... + all(next_states(1,:)==next_states(3,:)) + fprintf('Assertion: Invalid state.\n'); + end + + % Update states + obj.States = next_states; + obj.StepCount = obj.StepCount + 1; + + % plot the environment + if obj.StepCount <= obj.MaxStepCount + plot(obj); + end + + end + + function resetImpl(obj) + % Initialize / reset discrete-state properties + + % set unexplored cells + obj.Grid = zeros(obj.Size); + + % set obstacle cells + if ~isequal(obj.Obstacles,-1) + for idx = 1:size(obj.Obstacles,1) + r = obj.Obstacles(idx,1); + c = obj.Obstacles(idx,2); + obj.Grid(r,c) = 1.0; + end + end + + % set step count + obj.StepCount = 0; + + % explored cells + obj.NumExploredCells = ones(1,3); + + % set robot cells + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + obj.Grid(sA(1),sA(2)) = 0.25; + obj.Grid(sB(1),sB(2)) = 0.50; + obj.Grid(sC(1),sC(2)) = 0.75; + obj.States = obj.InitialStates; + end + + %% Backup/restore functions + function s = saveObjectImpl(obj) + % Set properties in structure s to values in object obj + + % Set public properties and states + s = saveObjectImpl@matlab.System(obj); + + % Set private and protected properties + %s.myproperty = obj.myproperty; + end + + function loadObjectImpl(obj,s,wasLocked) + % Set properties in object obj to values in structure s + + % Set private and protected properties + % obj.myproperty = s.myproperty; + + % Set public properties and states + loadObjectImpl@matlab.System(obj,s,wasLocked); + end + + %% Simulink functions + function ds = getDiscreteStateImpl(obj) + % Return structure of properties with DiscreteState attribute + ds.Grid = obj.Grid; + ds.States = obj.States; + ds.StepCount = obj.StepCount; + ds.NumExploredCells = obj.NumExploredCells; + end + + function flag = isInputSizeMutableImpl(obj,index) %#ok + % Return false if input size cannot change + % between calls to the System object + flag = false; + end + + function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok + % Return size for each output port +% out1 = [12 12 4 3]; % observation + out1 = [64 64 4]; % observation + out2 = [1]; % reward + out3 = [ 1]; % isdone + end + + function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok + % Return data type for each output port + out1 = "double"; + out2 = "double"; + out3 = "double"; + end + + function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok + % Return true for each output port with complex data + out1 = false; + out2 = false; + out3 = false; + end + + function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok + % Return true for each output port with fixed size + out1 = true; + out2 = true; + out3 = true; + end + + function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name) + % Return size, data type, and complexity of discrete-state + % specified in name + if strcmpi(name,'Grid') + sz = obj.Size; + dt = "double"; + cp = false; + elseif strcmpi(name,'States') + sz = [3 2]; + dt = "double"; + cp = false; + elseif strcmpi(name,'StepCount') + sz = [1 1]; + dt = "double"; + cp = false; + elseif strcmpi(name,'NumExploredCells') + sz = [1 3]; + dt = "double"; + cp = false; + else + error(['Error: Incorrect State Name: ', name.']); + end + end + + function icon = getIconImpl(obj) %#ok + % Define icon for System block + icon = mfilename("class"); % Use class name + end + end + + methods(Static, Access = protected) + %% Simulink customization functions + function header = getHeaderImpl + % Define header panel for System block dialog + header = matlab.system.display.Header(mfilename("class")); + end + + function group = getPropertyGroupsImpl + % Define property section(s) for System block dialog + group = matlab.system.display.Section(mfilename("class")); + end + + end + + methods(Access=private) + function collision = checkCollision(obj,new_state,other_states) + % Create array of occupied states + if isequal(obj.Obstacles,-1) + occupiedStates = other_states; + else + occupiedStates = [other_states; obj.Obstacles]; + end + % check collision + collision = any(all(new_state==occupiedStates,2)); + end + + function plot(obj) + persistent ax cells robots + + if isempty(ax) || ~isvalid(ax) + % build figure + f = figure; + f.Position = [195 120 400 300]; + %f.Visible = 'on'; % force external figure + ax = gca(f); + hold(ax,'on'); + if ~isequal(obj.Obstacles,-1) + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + else + cmap = [255 255 255;... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + ]./255; % black (obstacles) + end + colormap(ax,cmap); + + % plot cells + cdata = obj.Grid; + cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata); + + % plot grid lines + x = 0:1:obj.Size(2); + y = 0:1:obj.Size(1); + [X,Y] = meshgrid(x,y); + plot(ax,X,Y,'Color',[0.94 0.94 0.94]); + plot(ax,Y,X,'Color',[0.94 0.94 0.94]); + + % plot robots + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + robots = gobjects(1,2); + robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1); + robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1); + robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1); + + % time text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage)); + + ax.XTick = 0:1:obj.Size(1); + ax.YTick = 0:1:obj.Size(2); + ax.XTickLabel = {}; + ax.YTickLabel = {}; + axis(ax,'equal'); + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + ax.Box = 'on'; + end + + % update color map + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + if all(obj.Grid~=0,'all') + cmap = cmap(2:end,:); % no unexplored cells + end + if isequal(obj.Obstacles,-1) + cmap = cmap(1:end-1,:); % no obstacles + end + colormap(ax,cmap); + + % update cell colors + cdata = obj.Grid; + cells.CData = cdata; + + % update robot positions + for idx = 1:3 + s = obj.States(idx,:); + robots(idx).Position = [s(2)-1 s(1)-1 1 1]; + end + + % update info text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage); + + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + 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L_#T+y= + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + % Implement algorithm. Calculate y as a function of input u and + % discrete states. + + numRobots = 1; + + % Rewards are: + + % Agent moves to Terminal State: 10 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% case 0 +% % Wait +% next_states(idx,:) = state; +% rewards(idx) = rewards(idx) - 10; % lazy penalty + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + + case 1 + % Move up North + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down South + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move left WEst + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move right East + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 5 + % Move right-up NorthEast + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + + case 6 + % Move Left up NorthWest + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 7 + % Move Right Down South East + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 8 + % Move Left Down South West + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + end + end + + + % update grid and reward agents for new exploration + for idx = 1:numRobots + r = next_states(idx,1); + c = next_states(idx,2); + if obj.Grid(r,c) == 0.0 + % robot explores an unexplored cell + rewards(idx) = rewards(idx) + 20; + % update grid values + switch(idx) + case 1 + obj.Grid(r,c) = 0.25; % explored by A + obj.NumExploredCells = obj.NumExploredCells + [1 0 0]; + case 2 + obj.Grid(r,c) = 0.5; % explored by B + obj.NumExploredCells = obj.NumExploredCells + [0 1 0]; + case 3 + obj.Grid(r,c) = 0.75; % explored by C + obj.NumExploredCells = obj.NumExploredCells + [0 0 1]; + end + end + end + + % coverage metrics +% totalExploredCells = sum(obj.NumExploredCells); +% totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); +% if totalExploredCells >= totalCells +% isdone = 1; +% rewards = rewards + 4000 * (totalExploredCells'/totalCells); +% end + + % Observation for each agent is a 12x12 4-channel image. The + % channels are: + % 1. Obstacle channel - cells with obstacles are 1, rest 0 + % 2. Self channel - cell with the agent's state is 1, rest 0 + % 3. Friend channel - cell with other agent's state is 1, rest 0 + % 4. Coverage channel - cells that are unexplored are 1, rest 0 + observations = zeros(obj.Size(1),obj.Size(2),4,numRobots); + for idx = 1:numRobots + obstacleChannel = 1.0 * (obj.Grid == 1.0); + + selfIdx = idx; + selfRow = next_states(selfIdx,1); + selfCol = next_states(selfIdx,2); + selfChannel = zeros(obj.Size); + selfChannel(selfRow,selfCol) = 1.0; + + friendIdxs = idx ~= (1:numRobots); + friendRows = next_states(friendIdxs,1); + friendCols = next_states(friendIdxs,2); + friendChannel = zeros(obj.Size); + friendChannel(friendRows(1),friendCols(1)) = 1.0; + friendChannel(friendRows(2),friendCols(2)) = 1.0; + + coverageChannel = 1.0 * (obj.Grid == 0); + + observations(:,:,1,idx) = obstacleChannel; + observations(:,:,2,idx) = selfChannel; + observations(:,:,3,idx) = friendChannel; + observations(:,:,4,idx) = coverageChannel; + end + + % Scale down rewards + rewards = rewards./20; + + % DEBUG + if all(next_states(1,:)==next_states(2,:)) || ... + all(next_states(2,:)==next_states(3,:)) || ... + all(next_states(1,:)==next_states(3,:)) + fprintf('Assertion: Invalid state.\n'); + end + + % Update states + obj.States = next_states; + obj.StepCount = obj.StepCount + 1; + + % plot the environment + if obj.StepCount <= obj.MaxStepCount + plot(obj); + end + + end + + function resetImpl(obj) + % Initialize / reset discrete-state properties + + % set unexplored cells + obj.Grid = zeros(obj.Size); + + % set obstacle cells + if ~isequal(obj.Obstacles,-1) + for idx = 1:size(obj.Obstacles,1) + r = obj.Obstacles(idx,1); + c = obj.Obstacles(idx,2); + obj.Grid(r,c) = 1.0; + end + end + + % set step count + obj.StepCount = 0; + + % explored cells + obj.NumExploredCells = ones(1,3); + + % set robot cells + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + obj.Grid(sA(1),sA(2)) = 0.25; + obj.Grid(sB(1),sB(2)) = 0.50; + obj.Grid(sC(1),sC(2)) = 0.75; + obj.States = obj.InitialStates; + end + + %% Backup/restore functions + function s = saveObjectImpl(obj) + % Set properties in structure s to values in object obj + + % Set public properties and states + s = saveObjectImpl@matlab.System(obj); + + % Set private and protected properties + %s.myproperty = obj.myproperty; + end + + function loadObjectImpl(obj,s,wasLocked) + % Set properties in object obj to values in structure s + + % Set private and protected properties + % obj.myproperty = s.myproperty; + + % Set public properties and states + loadObjectImpl@matlab.System(obj,s,wasLocked); + end + + %% Simulink functions + function ds = getDiscreteStateImpl(obj) + % Return structure of properties with DiscreteState attribute + ds.Grid = obj.Grid; + ds.States = obj.States; + ds.StepCount = obj.StepCount; + ds.NumExploredCells = obj.NumExploredCells; + end + + function flag = isInputSizeMutableImpl(obj,index) %#ok + % Return false if input size cannot change + % between calls to the System object + flag = false; + end + + function [out1, out2, out3] = getOutputSizeImpl(obj) %#ok + % Return size for each output port + out1 = [12 12 4 3]; % observation + out2 = [3 1]; % reward + out3 = [1 1]; % isdone + end + + function [out1,out2,out3] = getOutputDataTypeImpl(obj) %#ok + % Return data type for each output port + out1 = "double"; + out2 = "double"; + out3 = "double"; + end + + function [out1,out2,out3] = isOutputComplexImpl(obj) %#ok + % Return true for each output port with complex data + out1 = false; + out2 = false; + out3 = false; + end + + function [out1,out2,out3] = isOutputFixedSizeImpl(obj) %#ok + % Return true for each output port with fixed size + out1 = true; + out2 = true; + out3 = true; + end + + function [sz,dt,cp] = getDiscreteStateSpecificationImpl(obj,name) + % Return size, data type, and complexity of discrete-state + % specified in name + if strcmpi(name,'Grid') + sz = obj.Size; + dt = "double"; + cp = false; + elseif strcmpi(name,'States') + sz = [3 2]; + dt = "double"; + cp = false; + elseif strcmpi(name,'StepCount') + sz = [1 1]; + dt = "double"; + cp = false; + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% elseif strcmpi(name,'NumExploredCells') +% sz = [1 3]; +% dt = "double"; +% cp = false; + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + + else + error(['Error: Incorrect State Name: ', name.']); + end + end + + function icon = getIconImpl(obj) %#ok + % Define icon for System block + icon = mfilename("class"); % Use class name + end + end + + methods(Static, Access = protected) + %% Simulink customization functions + function header = getHeaderImpl + % Define header panel for System block dialog + header = matlab.system.display.Header(mfilename("class")); + end + + function group = getPropertyGroupsImpl + % Define property section(s) for System block dialog + group = matlab.system.display.Section(mfilename("class")); + end + + end + + methods(Access=private) + function collision = checkCollision(obj,new_state,other_states) + % Create array of occupied states + if isequal(obj.Obstacles,-1) + occupiedStates = other_states; + else + occupiedStates = [other_states; obj.Obstacles]; + end + % check collision + collision = any(all(new_state==occupiedStates,2)); + end + + function plot(obj) + persistent ax cells robots + + if isempty(ax) || ~isvalid(ax) + % build figure + f = figure; + f.Position = [195 120 400 300]; + %f.Visible = 'on'; % force external figure + ax = gca(f); + hold(ax,'on'); + if ~isequal(obj.Obstacles,-1) + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + else + cmap = [255 255 255;... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + ]./255; % black (obstacles) + end + colormap(ax,cmap); + + % plot cells + cdata = obj.Grid; + cells = imagesc(ax,[0.5 obj.Size(1)-0.5],[0.5 obj.Size(2)-0.5],cdata); + + % plot grid lines + x = 0:1:obj.Size(2); + y = 0:1:obj.Size(1); + [X,Y] = meshgrid(x,y); + plot(ax,X,Y,'Color',[0.94 0.94 0.94]); + plot(ax,Y,X,'Color',[0.94 0.94 0.94]); + + % plot robots + sA = obj.InitialStates(1,:); + sB = obj.InitialStates(2,:); + sC = obj.InitialStates(3,:); + robots = gobjects(1,2); + robots(1) = rectangle(ax,'Position',[sA(2)-1 sA(1)-1 1 1],'FaceColor','r','Curvature',1); + robots(2) = rectangle(ax,'Position',[sB(2)-1 sB(1)-1 1 1],'FaceColor','g','Curvature',1); + robots(3) = rectangle(ax,'Position',[sC(2)-1 sC(1)-1 1 1],'FaceColor','b','Curvature',1); + + % time text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + title(ax,sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage)); + + ax.XTick = 0:1:obj.Size(1); + ax.YTick = 0:1:obj.Size(2); + ax.XTickLabel = {}; + ax.YTickLabel = {}; + axis(ax,'equal'); + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + ax.Box = 'on'; + end + + % update color map + cmap = [255 255 255; ... % white (unexplored) + 255 140 105; ... % light red (explored by A) + 152 251 152; ... % light green (explored by B) + 176 226 255; ... % light blue (explored by C) + 0 0 0]./255; % black (obstacles) + if all(obj.Grid~=0,'all') + cmap = cmap(2:end,:); % no unexplored cells + end + if isequal(obj.Obstacles,-1) + cmap = cmap(1:end-1,:); % no obstacles + end + colormap(ax,cmap); + + % update cell colors + cdata = obj.Grid; + cells.CData = cdata; + + % update robot positions + for idx = 1:2 + s = obj.States(idx,:); + robots(idx).Position = [s(2)-1 s(1)-1 1 1]; + end + + % update info text + totalExploredCells = sum(obj.NumExploredCells); + totalCells = obj.Size(1) * obj.Size(2) - sum(obj.Grid==1,'all'); + coverage = totalExploredCells / totalCells * 100; + ax.Title.String = sprintf('Steps = %d, Coverage = %.1f%%',obj.StepCount,coverage); + + ax.XLim = [0 obj.Size(1)]; + ax.YLim = [0 obj.Size(2)]; + grid(ax,'on'); + + drawnow(); + end + end +end diff --git a/CustomGridWorldV0.m b/CustomGridWorldV0.m new file mode 100644 index 0000000..f44149e --- /dev/null +++ b/CustomGridWorldV0.m @@ -0,0 +1,211 @@ +classdef CustomGridWorldV0 < matlab.System + % GridWorld represents a 12x12 deterministic grid world with 3 robots. + +% Copyright 2020-2022 The MathWorks, Inc. + + % Public, tunable properties +% properties +% % Initial position of robots +% InitialStates (1,2) double +% +% +% end + + properties(Dependent) + % Initial position of robots + InitialStates (1,2) double + + % CurrentState + % String with name of current state +% CurrentState string + + % States + % String vector of the state names + States string + + % Actions + % String vector with the action names + Actions string + + % ObstacleStates + % String vector with the state names which can not be reached in + % the grid world. + ObstacleStates string + + % TerminalStates + % String vector with the state names which are terminal in the grid + % world. + TerminalStates string + + + % add terminal + end + + % Public, non-tunable properties + properties (Nontunable) + % Obstacle matrix + Obstacles double = -1 + % Max step count + MaxStepCount (1,1) double = 500 + + %%%&&&&&&&&&&&&&&&&&&& +% TerminalStates (1,2) double % add terminal + %%%%%%%%%%%%%%%%%%%%%%%%%%% + end + + properties(DiscreteState) + % Discretized XY space with cells containing 0.5 or 1.0 + % 0: unexplored + % 0.25: explored by robot A + % 0.50: explored by robot B + % 0.75: explored by robot B + % 1.0: obstacle + Grid + % States of robot A,B: [rowA colA; rowB colB] +% States + % Step count + StepCount + % Individual cell exploration count +% NumExploredCells + end + + % Pre-computed constants + properties(Access = private) + % Handle to figure +% Figure + % Grid size [numrows numcols] + Size (1,2) double + end + + methods + % Constructor + function this = CustomGridWorldV0(varargin) + % Support name-value pair arguments when constructing object + setProperties(this,nargin,varargin{:}) + end + end + + methods(Access = protected) + %% Common functions + function setupImpl(obj) %#ok + % Perform one-time calculations, such as computing constants + end + + function [observations,rewards,isdone] = stepImpl(obj,actions) + numRobots = 1; + + % Rewards are: + + % Agent moves to Terminal State: 10 + % Agent tries to move out of grid: -10 + % Agent collides with another agent: -10 + % Agent collides with obstacle: -10 + % Movement penalty: -1 + % Lazy penalty: -2 + % On full coverage: +4000 * coverage contribution + + % move robots to their next state + %next_states = zeros(numRobots,2); + rewards = zeros(numRobots,1); + isdone = 0; + next_states = obj.States; + for idx = 1:numRobots + state = obj.States(idx,:); + action = actions(idx); + switch(action) +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + +% case 0 +% % Wait +% next_states(idx,:) = state; +% rewards(idx) = rewards(idx) - 10; % lazy penalty + +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + + case 1 + % Move up North + if state(1) < obj.Size(1) && ~checkCollision(obj,state+[1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go up + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 2 + % Move down South + if state(1) > 1 && ~checkCollision(obj,state+[-1 0],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 0]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go down + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 4 + % Move left WEst + if state(2) > 1 && ~checkCollision(obj,state+[0 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go left + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 3 + % Move right East + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[0 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [0 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 5 + % Move right-up NorthEast + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + + case 6 + % Move Left up NorthWest + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 7 + % Move Right Down South East + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + case 8 + % Move Left Down South West + if state(2) < obj.Size(2) && ~checkCollision(obj,state+[-1 -1],next_states(idx~=1:numRobots,:)) + next_states(idx,:) = state + [-1 -1]; + rewards(idx) = rewards(idx) - 1; + else + % add a negative reward for trying to go right + next_states(idx,:) = state; + rewards(idx) = rewards(idx) - 10; + end + end + end + end + end +end \ No newline at end of file diff --git a/DQNtrainedAgents.mat b/DQNtrainedAgents.mat new file mode 100644 index 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