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Eric Liang 5f430da180 [rllib] Provide internal access to episode state in compute_actions() and allow returning extra batches (#2559 )

The goal of this PR is to allow custom policies to perform model-based rollouts. In the multi-agent setting, this requires access to not only policies of other agents, but also their current observations.
Also, you might want to return the model-based trajectories as part of the rollout for efficiency.

  compute_actions() now takes a new keyword arg episodes
  pull out internal episode class into a top-level file
  add function to return extra trajectories from an episode that will be appended to the sample batch
  documentation

2018-08-16 14:37:21 -07:00

_build

Get Sphinx infrastructure in place

2016-07-01 18:21:02 -07:00

source

[rllib] Provide internal access to episode state in compute_actions() and allow returning extra batches (#2559 )

2018-08-16 14:37:21 -07:00

make.bat

Get Sphinx infrastructure in place

2016-07-01 18:21:02 -07:00

Makefile

Move documentation to ReadTheDocs. (#326 )

2017-02-27 21:14:31 -08:00

README.md

Only install ray python packages. (#330 )

2017-03-01 23:34:44 -08:00

requirements-doc.txt

Change ray.worker.cleanup -> ray.shutdown and improve API documentation. (#2374 )

2018-07-12 12:00:00 -07:00

README.md

Ray Documentation

To compile the documentation, run the following commands from this directory. Note that Ray must be installed first.

pip install -r requirements-doc.txt
make html
open _build/html/index.html

To test if there are any build errors with the documentation, do the following.

sphinx-build -W -b html -d _build/doctrees source _build/html