l2rpn-baselines
bd-dev

How to contribute

  • Template: How to contribute to l2rpn baselines
  • Do Nothing: a more concrete example the “do nothing” Baseline

Some RL implementation examples

  • PPO: with ray/rllib
  • PPO: with stable-baselines3
  • External Contributions

Expert systems and optimizers

  • ExpertAgent: A example implementation of using ExpertOpForGrid for empirical overflow solving
  • OptimCVXPY: A example implementation of an agent based on an optimizer

Legacy implementations

  • utils: Some utility functions and classes
  • DeepQSimple: A simple implementation of the Deep Q Learning
  • DoubleDuelingDQN: A example implementation of Double Duelling Deep Q Network
  • DuelQSimple: Double Duelling Deep Q Learning
  • DuelQLeapNet: D3QN with LeapNet
  • DoubleDuelingRDQN: A example implementation of Recurrent DoubleQ Network
  • LeapNetEncoded: D3QN on a state encoded by a leap net
  • SAC: Soft Actor Critic
l2rpn-baselines
  • Python Module Index

Python Module Index

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- l2rpn_baselines
    l2rpn_baselines.DeepQSimple
    l2rpn_baselines.DoNothing
    l2rpn_baselines.DoubleDuelingDQN
    l2rpn_baselines.DoubleDuelingDQN.doubleDuelingDQNConfig.DoubleDuelingDQNConfig
    l2rpn_baselines.DoubleDuelingRDQN
    l2rpn_baselines.DoubleDuelingRDQN.doubleDuelingRDQNConfig.DoubleDuelingRDQNConfig
    l2rpn_baselines.DuelQLeapNet
    l2rpn_baselines.DuelQSimple
    l2rpn_baselines.ExpertAgent.ExpertAgent
    l2rpn_baselines.LeapNetEncoded
    l2rpn_baselines.PPO_RLLIB
    l2rpn_baselines.PPO_SB3
    l2rpn_baselines.SACOld
    l2rpn_baselines.Template
    l2rpn_baselines.utils

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