Ms Pac-Man Competition
Ms Pac-Man Competition (screen-capture version) IEEE CIG 2011 Results IEEE CIG 2010 Results IEEE CIG 2009 Results IEEE CEC 2009 Results WCCI 2008 Results CEC 2007 Results See also: Ms Pac-Man versus ghost-team competition. Introduction Latest news: IEEE CIG 2011 Results now available. The aim of this competition is to provide the best software controller for the game of Ms Pac-Man. This is a grea
Reinforcement Learning Simulator
Reinforcement Learning - Simulator Introduction The motivation behind this work is to simulate and animate the Reinforcement Learning algorithms to be able to better understand their behavior, which will enable to enhancements to these algorithms. Visualization is a better way of presenting new concepts to others. Our perception about animating these algorithms is to enable the students to get an
RL FAQ
Reinforcement Learning FAQ: Frequently Asked Questions about Reinforcement Learning Edited by Rich Sutton Initiated 8/13/01 Last updated 2/4/04 I get many questions about reinforcement learning -- how to think about it and how do it successfully in practice. This FAQ is an attempt to pull together in one place some of the more common questions and answers. I have been free with my opinio
Temporal difference learning - Wikipedia
Temporal difference (TD) learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. These methods sample from the environment, like Monte Carlo methods, and perform updates based on current estimates, like dynamic programming methods.[1] While Monte Carlo methods only adjust their estimates once the final ou
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小林(重)研究室 - 参考文献
autonweb:14686 [Auton Lab]
RLApplications.bib
RL-Glue 3.0 Technical Details
http://www.cs.ualberta.ca/~sutton/Talks/RL-Tutorial/sld001.htm
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A Short Introduction To Some RL Algorithms - Hado van Hasselt