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ray/rllib/contrib
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gjoliver 99a0088233
[RLlib] Unify the way we create local replay buffer for all agents (#19627) 
* [RLlib] Unify the way we create and use LocalReplayBuffer for all the agents.

This change
1. Get rid of the try...except clause when we call execution_plan(),
   and get rid of the Deprecation warning as a result.
2. Fix the execution_plan() call in Trainer._try_recover() too.
3. Most importantly, makes it much easier to create and use different types
   of local replay buffers for all our agents.
   E.g., allow us to easily create a reservoir sampling replay buffer for
   APPO agent for Riot in the near future.
* Introduce explicit configuration for replay buffer types.
* Fix is_training key error.
* actually deprecate buffer_size field.
2021-10-26 20:56:02 +02:00
..
alpha_zero [RLlib] Unify the way we create local replay buffer for all agents (#19627) 2021-10-26 20:56:02 +02:00
bandits [RLlib] Unify all RLlib Trainer.train() -> results[info][learner][policy ID][learner_stats] and add structure tests. (#18879) 2021-09-30 16:39:05 +02:00
maddpg [RLlib] Unify all RLlib Trainer.train() -> results[info][learner][policy ID][learner_stats] and add structure tests. (#18879) 2021-09-30 16:39:05 +02:00
random_agent [tune] Use public methods for trainable (#9184) 2020-07-01 11:00:00 -07:00
sumo [Lint] Add flake8-bugbear (#19053) 2021-10-03 23:24:11 -07:00
__init__.py [rllib] Try moving RLlib to top level dir (#5324) 2019-08-05 23:25:49 -07:00
README.rst [docs] Move all /latest links to /master (#11897) 2020-11-10 10:53:28 -08:00
registry.py [RLlib] Allow rllib rollout to run distributed via evaluation workers. (#13718) 2021-02-08 12:05:16 +01:00

README.rst 

Contributed algorithms, which can be run via ``rllib train --run=contrib/<alg_name>``

See https://docs.ray.io/en/master/rllib-dev.html for guidelines.