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ray/rllib/agents/sac/README.md
Sven Mika 510c850651
[RLlib] SAC add discrete action support. (#7320) 
* Exploration API (+EpsilonGreedy sub-class).

* Exploration API (+EpsilonGreedy sub-class).

* Cleanup/LINT.

* Add `deterministic` to generic Trainer config (NOTE: this is still ignored by most Agents).

* Add `error` option to deprecation_warning().

* WIP.

* Bug fix: Get exploration-info for tf framework.
Bug fix: Properly deprecate some DQN config keys.

* WIP.

* LINT.

* WIP.

* Split PerWorkerEpsilonGreedy out of EpsilonGreedy.
Docstrings.

* Fix bug in sampler.py in case Policy has self.exploration = None

* Update rllib/agents/dqn/dqn.py

Co-Authored-By: Eric Liang <ekhliang@gmail.com>

* WIP.

* Update rllib/agents/trainer.py

Co-Authored-By: Eric Liang <ekhliang@gmail.com>

* WIP.

* Change requests.

* LINT

* In tune/utils/util.py::deep_update() Only keep deep_updat'ing if both original and value are dicts. If value is not a dict, set

* Completely obsolete syn_replay_optimizer.py's parameters schedule_max_timesteps AND beta_annealing_fraction (replaced with prioritized_replay_beta_annealing_timesteps).

* Update rllib/evaluation/worker_set.py

Co-Authored-By: Eric Liang <ekhliang@gmail.com>

* Review fixes.

* Fix default value for DQN's exploration spec.

* LINT

* Fix recursion bug (wrong parent c'tor).

* Do not pass timestep to get_exploration_info.

* Update tf_policy.py

* Fix some remaining issues with test cases and remove more deprecated DQN/APEX exploration configs.

* Bug fix tf-action-dist

* DDPG incompatibility bug fix with new DQN exploration handling (which is imported by DDPG).

* Switch off exploration when getting action probs from off-policy-estimator's policy.

* LINT

* Fix test_checkpoint_restore.py.

* Deprecate all SAC exploration (unused) configs.

* Properly use `model.last_output()` everywhere. Instead of `model._last_output`.

* WIP.

* Take out set_epsilon from multi-agent-env test (not needed, decays anyway).

* WIP.

* Trigger re-test (flaky checkpoint-restore test).

* WIP.

* WIP.

* Add test case for deterministic action sampling in PPO.

* bug fix.

* Added deterministic test cases for different Agents.

* Fix problem with TupleActions in dynamic-tf-policy.

* Separate supported_spaces tests so they can be run separately for easier debugging.

* LINT.

* Fix autoregressive_action_dist.py test case.

* Re-test.

* Fix.

* Remove duplicate py_test rule from bazel.

* LINT.

* WIP.

* WIP.

* SAC fix.

* SAC fix.

* WIP.

* WIP.

* WIP.

* FIX 2 examples tests.

* WIP.

* WIP.

* WIP.

* WIP.

* WIP.

* Fix.

* LINT.

* Renamed test file.

* WIP.

* Add unittest.main.

* Make action_dist_class mandatory.

* fix

* FIX.

* WIP.

* WIP.

* Fix.

* Fix.

* Fix explorations test case (contextlib cannot find its own nullcontext??).

* Force torch to be installed for QMIX.

* LINT.

* Fix determine_tests_to_run.py.

* Fix determine_tests_to_run.py.

* WIP

* Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function).

* Add Random exploration component to tests (fixed issue with "static-graph randomness" via py_function).

* Rename some stuff.

* Rename some stuff.

* WIP.

* update.

* WIP.

* Gumbel Softmax Dist.

* WIP.

* WIP.

* WIP.

* WIP.

* WIP.

* WIP.

* WIP

* WIP.

* WIP.

* Hypertune.

* Hypertune.

* Hypertune.

* Lock-in.

* Cleanup.

* LINT.

* Fix.

* Update rllib/policy/eager_tf_policy.py

Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com>

* Update rllib/agents/sac/sac_policy.py

Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com>

* Update rllib/agents/sac/sac_policy.py

Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com>

* Update rllib/models/tf/tf_action_dist.py

Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com>

* Update rllib/models/tf/tf_action_dist.py

Co-Authored-By: Kristian Hartikainen <kristian.hartikainen@gmail.com>

* Fix items from review comments.

* Add dm_tree to RLlib dependencies.

* Add dm_tree to RLlib dependencies.

* Fix DQN test cases ((Torch)Categorical).

* Fix wrong pip install.

Co-authored-by: Eric Liang <ekhliang@gmail.com>
Co-authored-by: Kristian Hartikainen <kristian.hartikainen@gmail.com>
2020-03-06 10:37:12 -08:00

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Implementation of the Soft Actor-Critic algorithm:

[1] Soft Actor-Critic Algorithms and Applications - T. Haarnoja, A. Zhou, K. Hartikainen, et. al https://arxiv.org/abs/1812.05905.pdf

For supporting discrete action spaces, we implemented this patch on top of the original algorithm: [2] Soft Actor-Critic for Discrete Action Settings - Petros Christodoulou https://arxiv.org/pdf/1910.07207v2.pdf