Artificial Intelligence


Rebellious Reinforcement Learning

Authors: Joy Chopra

Actor critic methods have shown good performance in reinforcement learning domain. We propose using rebellious policy i.e. taking action with minimum Q value to enhance exploration and let the critic understand why other actions are good or may be not?! We will now propose the rest of the paper. NO we will not.

Comments: 1 Page.

Download: PDF

Submission history

[v1] 2018-09-27 02:08:06

Unique-IP document downloads: 38 times is a pre-print repository rather than a journal. Articles hosted may not yet have been verified by peer-review and should be treated as preliminary. In particular, anything that appears to include financial or legal advice or proposed medical treatments should be treated with due caution. will not be responsible for any consequences of actions that result from any form of use of any documents on this website.

Add your own feedback and questions here:
You are equally welcome to be positive or negative about any paper but please be polite. If you are being critical you must mention at least one specific error, otherwise your comment will be deleted as unhelpful.

comments powered by Disqus