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* initial ACER commit * Code cleanup + several fixes * Q-retrace bug fix + small clean-ups * added documentation for acer * ACER benchmarks * update benchmarks table * Add nightly running of golden and trace tests. (#202) Resolves #200 * comment out nightly trace tests until values reset. * remove redundant observe ignore (#168) * ensure nightly test env containers exist. (#205) Also bump integration test timeout * wxPython removal (#207) Replacing wxPython with Python's Tkinter. Also removing the option to choose multiple files as it is unused and causes errors, and fixing the load file/directory spinner. * Create CONTRIBUTING.md (#210) * Create CONTRIBUTING.md. Resolves #188 * run nightly golden tests sequentially. (#217) Should reduce resource requirements and potential CPU contention but increases overall execution time. * tests: added new setup configuration + test args (#211) - added utils for future tests and conftest - added test args * new docs build * golden test update
45 lines
1.1 KiB
ReStructuredText
45 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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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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