Algorithms¶
d3rlpy provides state-of-the-art data-driven deep reinforcement learning algorithms as well as online algorithms for the base implementations.
Continuous control algorithms¶
d3rlpy.algos.BC |
Behavior Cloning algorithm. |
d3rlpy.algos.DDPG |
Deep Deterministic Policy Gradients algorithm. |
d3rlpy.algos.TD3 |
Twin Delayed Deep Deterministic Policy Gradients algorithm. |
d3rlpy.algos.SAC |
Soft Actor-Critic algorithm. |
d3rlpy.algos.BCQ |
Batch-Constrained Q-learning algorithm. |
d3rlpy.algos.BEAR |
Bootstrapping Error Accumulation Reduction algorithm. |
d3rlpy.algos.CQL |
Conservative Q-Learning algorithm. |
d3rlpy.algos.AWR |
Advantage-Weighted Regression algorithm. |
d3rlpy.algos.AWAC |
Advantage Weighted Actor-Critic algorithm. |
Discrete control algorithms¶
d3rlpy.algos.DiscreteBC |
Behavior Cloning algorithm for discrete control. |
d3rlpy.algos.DQN |
Deep Q-Network algorithm. |
d3rlpy.algos.DoubleDQN |
Double Deep Q-Network algorithm. |
d3rlpy.algos.DiscreteBCQ |
Discrete version of Batch-Constrained Q-learning algorithm. |
d3rlpy.algos.DiscreteCQL |
Discrete version of Conservative Q-Learning algorithm. |
d3rlpy.algos.DiscreteCQL |
Discrete version of Conservative Q-Learning algorithm. |
d3rlpy.algos.DiscreteAWR |
Discrete veriosn of Advantage-Weighted Regression algorithm. |