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74db141d5e
* SAC algorithm * SAC - updates to agent (learn_from_batch), sac_head and sac_q_head to fix problem in gradient calculation. Now SAC agents is able to train. gym_environment - fixing an error in access to gym.spaces * Soft Actor Critic - code cleanup * code cleanup * V-head initialization fix * SAC benchmarks * SAC Documentation * typo fix * documentation fixes * documentation and version update * README typo
46 lines
1.1 KiB
ReStructuredText
46 lines
1.1 KiB
ReStructuredText
Agents
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======
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Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes -
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value optimization, policy optimization and imitation learning.
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A detailed description of those algorithms can be found by navigating to each of the algorithm pages.
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.. image:: /_static/img/algorithms.png
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:width: 600px
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:align: center
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.. toctree::
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:maxdepth: 1
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:caption: Agents
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policy_optimization/ac
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policy_optimization/acer
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imitation/bc
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value_optimization/bs_dqn
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value_optimization/categorical_dqn
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imitation/cil
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policy_optimization/cppo
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policy_optimization/ddpg
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policy_optimization/sac
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other/dfp
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value_optimization/double_dqn
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value_optimization/dqn
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value_optimization/dueling_dqn
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value_optimization/mmc
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value_optimization/n_step
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value_optimization/naf
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value_optimization/nec
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value_optimization/pal
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policy_optimization/pg
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policy_optimization/ppo
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value_optimization/rainbow
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value_optimization/qr_dqn
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.. autoclass:: rl_coach.base_parameters.AgentParameters
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.. autoclass:: rl_coach.agents.agent.Agent
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:members:
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:inherited-members:
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