Skip to content

Latest commit

 

History

History
42 lines (33 loc) · 2.26 KB

README.md

File metadata and controls

42 lines (33 loc) · 2.26 KB
Raw

Configuration Details for BricksRL Experiments

Overview

This directory contains all the necessary configuration files to tailor your experiments using BricksRL. Configurations are managed using Hydra, a powerful tool for configuring complex applications that allows for easy modification of parameters directly from the command line.

Configuration Files

  • config.yaml: The base configuration for all experiments including what agent and environment to run.
  • env/: Contains environment-specific configurations.
    • runaway-v0.yaml: Settings for the RunAway-v0 environment for the 2wheeler robot.
    • spinning-v0.yaml: Settings for the Spinning-v0 environment for the 2wheeler robot.
    • walker-v0.yaml: Settings for the Walker-v0 environment for the walker robot.
    • walker_sim-v0.yaml: Settings for the WalkerSim-v0 environment for the walker robot.
    • roboarm-v0.yaml: Settings for the RoboArm-v0 environment for the roboarm robot.
    • roboarm_sim-v0.yaml: Settings for the RoboArmSim-v0 environment for the roboarm robot.
    • roboarm_mixed-v0.yaml: Settings for the RoboArmMixed-v0 environment for the roboarm robot.
  • agent/: Contains agent-specific configurations.
    • sac.yaml: Configuration for the SAC agent.
    • td3.yaml: Configuration for the TD3 agent.
    • droq.yaml: Configuration for the DroQ agent.

Using Hydra for Configuration Overrides

Hydra allows you to override any configuration parameter directly from the terminal when you run your experiments. This makes it easy to test different configurations without altering your configuration files.

Example Usage

To run an experiment with the walker environment using the SAC agent and specify the number of episodes directly from the command line, you can use the following command:

python experiments/walker/train.py episodes=200 agent=sac

This command temporarily overrides the episodes and agent parameters for this specific run without needing to change the configuration files.

You can further override agent or environment specific parameter like:

python experiments/walker/train.py agent=sac agent.batch_size=32

or

python experiments/walker/train.py env.max_episode_steps=200 env.frame_stack=4