wassname/ray
1
0
Fork 0
mirror of https://github.com/wassname/ray.git synced 2026-09-09 11:32:43 +08:00
Code Issues Packages Projects Releases Wiki Activity

[rllib] add blog posts to examples list (#5762)

Browse Source 
* add blog post

* remove

* link
This commit is contained in:
Eric Liang
2019-09-23 10:42:21 -07:00
committed by GitHub
parent 61e5d674be
commit 249ca2cf9e
3 changed files with 9 additions and 5 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/source/rllib-env.rst
-4
View File
@@ -130,10 +130,6 @@ When using remote envs, you can control the batching level for inference with ``
Multi-Agent and Hierarchical
----------------------------
.. note::
Learn more about multi-agent reinforcement learning in RLlib by checking out some of the `code examples <rllib-examples.html#multi-agent-and-hierarchical>`__ or reading the `blog post <https://bair.berkeley.edu/blog/2018/12/12/rllib/>`__.
A multi-agent environment is one which has multiple acting entities per step, e.g., in a traffic simulation, there may be multiple "car" and "traffic light" agents in the environment. The model for multi-agent in RLlib as follows: (1) as a user you define the number of policies available up front, and (2) a function that maps agent ids to policy ids. This is summarized by the below figure:
.. image:: multi-agent.svg