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[RLlib] Agents to algos: DQN w/o Apex and R2D2, DDPG/TD3, SAC, SlateQ, QMIX, PG, Bandits #24896

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May 19, 2022
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[RLlib] Agents to algos: DQN w/o Apex and R2D2, DDPG/TD3, SAC, SlateQ, QMIX, PG, Bandits #24896

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marwil
May 12, 2022
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marwil BUILDs
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marwil
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dreamer
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alpha_star
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maml
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cql
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Merge branch 'master' of https://github.com/ray-project/ray into agen…
May 12, 2022
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added missing test from alpha_star
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removed playground.py
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Merge branch 'master' of https://github.com/ray-project/ray into agen…
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Merge branch 'master' of https://github.com/ray-project/ray into agen…
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Merge branch 'master' into agents-to-algos
May 17, 2022
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moved bandits
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moved pg
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moved dqn derivs
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wip dqn
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moved ddpg
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moved sac
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updated registry for sac and ddpg
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moved qmix
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moved slateq
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lint
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Merge branch 'master' of https://github.com/ray-project/ray into agen…
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wip
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wip
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added test_algorithm_imports to BUILD
May 19, 2022
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updated examples
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wip
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Merge branch 'master' into agents-to-algos
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kourosh_hakhamaneshi committed May 17, 2022
commit 95de00165cba81d9bb5efcbfdccae68c259d451c
10 changes: 5 additions & 5 deletions doc/source/rllib/rllib-algorithms.rst
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Expand Up @@ -711,14 +711,14 @@ regression model and uses this confidence ellipsoid to estimate the
uncertainty of action values.

Tuned examples:
`SimpleContextualBandit <https://github.com/ray-project/ray/blob/master/rllib/agents/bandit/tests/test_bandits.py>`__,
`SimpleContextualBandit <https://github.com/ray-project/ray/blob/master/rllib/algorithms/bandit/tests/test_bandits.py>`__,
`UCB Bandit on RecSim <https://github.com/ray-project/ray/blob/master/rllib/examples/bandit/tune_lin_ucb_train_recsim_env.py>`__.
`ParametricItemRecoEnv <https://github.com/ray-project/ray/blob/master/rllib/examples/bandit/tune_lin_ucb_train_recommendation.py>`__.

**LinUCB-specific configs** (see also `common configs <rllib-training
.html#common-parameters>`__):

.. literalinclude:: ../../../rllib/agents/bandit/bandit.py
.. literalinclude:: ../../../rllib/algorithms/bandit/bandit.py
:language: python
:start-after: __sphinx_doc_begin__
:end-before: __sphinx_doc_end__
Expand All @@ -730,7 +730,7 @@ Linear Thompson Sampling (BanditLinTSTrainer)
---------------------------------------------
|pytorch|
`[paper] <http://proceedings.mlr.press/v28/agrawal13.pdf>`__
`[implementation] <https://github.com/ray-project/ray/blob/master/rllib/agents/bandit/bandit.py>`__
`[implementation] <https://github.com/ray-project/ray/blob/master/rllib/algorithms/bandit/bandit.py>`__
Like LinUCB, LinTS also assumes a linear dependency between the expected
reward of an action and its context and uses online ridge regression to
estimate the Q values of actions given the context. It assumes a Gaussian
Expand All @@ -739,12 +739,12 @@ action to take, the agent samples weights for each arm, using
the posterior distributions, and plays the arm that produces the highest reward.

Tuned examples:
`SimpleContextualBandit <https://github.com/ray-project/ray/blob/master/rllib/agents/bandit/tests/test_bandits.py>`__,
`SimpleContextualBandit <https://github.com/ray-project/ray/blob/master/rllib/algorithms/bandit/tests/test_bandits.py>`__,
`WheelBandit <https://github.com/ray-project/ray/blob/master/rllib/examples/bandit/tune_lin_ts_train_wheel_env.py>`__.

**LinTS-specific configs** (see also `common configs <rllib-training.html#common-parameters>`__):

.. literalinclude:: ../../../rllib/agents/bandit/bandit.py
.. literalinclude:: ../../../rllib/algorithms/bandit/bandit.py
:language: python
:start-after: __sphinx_doc_begin__
:end-before: __sphinx_doc_end__
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