5c5a3db94e
This PR implements BCQPolicy, which could be used to train an offline agent in the environment of continuous action space. An experimental result 'halfcheetah-expert-v1' is provided, which is a d4rl environment (for Offline Reinforcement Learning). Example usage is in the examples/offline/offline_bcq.py.
147 lines
2.5 KiB
ReStructuredText
147 lines
2.5 KiB
ReStructuredText
tianshou.policy
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===============
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Base
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----
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.. autoclass:: tianshou.policy.BasePolicy
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.. autoclass:: tianshou.policy.RandomPolicy
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Model-free
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----------
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DQN Family
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~~~~~~~~~~
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.. autoclass:: tianshou.policy.DQNPolicy
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.. autoclass:: tianshou.policy.C51Policy
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.. autoclass:: tianshou.policy.RainbowPolicy
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.. autoclass:: tianshou.policy.QRDQNPolicy
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.. autoclass:: tianshou.policy.IQNPolicy
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.. autoclass:: tianshou.policy.FQFPolicy
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On-policy
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~~~~~~~~~
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.. autoclass:: tianshou.policy.PGPolicy
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.. autoclass:: tianshou.policy.NPGPolicy
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.. autoclass:: tianshou.policy.A2CPolicy
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.. autoclass:: tianshou.policy.TRPOPolicy
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.. autoclass:: tianshou.policy.PPOPolicy
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Off-policy
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~~~~~~~~~~
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.. autoclass:: tianshou.policy.DDPGPolicy
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.. autoclass:: tianshou.policy.TD3Policy
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.. autoclass:: tianshou.policy.SACPolicy
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.. autoclass:: tianshou.policy.DiscreteSACPolicy
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Imitation
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---------
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.. autoclass:: tianshou.policy.ImitationPolicy
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.. autoclass:: tianshou.policy.BCQPolicy
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.. autoclass:: tianshou.policy.DiscreteBCQPolicy
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.. autoclass:: tianshou.policy.DiscreteCQLPolicy
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.. autoclass:: tianshou.policy.DiscreteCRRPolicy
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Model-based
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-----------
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.. autoclass:: tianshou.policy.PSRLPolicy
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Multi-agent
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-----------
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.. autoclass:: tianshou.policy.MultiAgentPolicyManager
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