loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Sixth International Conference on Hybrid Intelligent Systems (HIS'06)
Emergence of Information Processor Using Real World--Real-Time Learning of Pursuit Problem
Auckland, New Zealand
December 13-December 15
ISBN: 0-7695-2662-4
Hiroyuki Fujii, Okayama University, Japan
Kazuyuki Ito, Hosei University, Japan
Akio Gofuku, Okayama University, Japan
Real-time reinforcement learning is difficult because number of trials is too much to complete learning within limited time.

To solve the problem, we consider reduction of action-state space by information processor using real world without prior knowledge. We obtain the information processor in evolution by setting the fitness as ease of learning. As a typical example, we address pursuit problem in which dynamics is regarded. As a result, the processor has been obtained in evolution and agent has learned in real-time.

Citation:
Hiroyuki Fujii, Kazuyuki Ito, Akio Gofuku, "Emergence of Information Processor Using Real World--Real-Time Learning of Pursuit Problem," his, pp.7, Sixth International Conference on Hybrid Intelligent Systems (HIS'06), 2006
Usage of this product signifies your acceptance of the Terms of Use.