1887

n South African Computer Journal - Evolving intelligent game-playing agents : research article

Volume 2004, Issue 32
  • ISSN : 1015-7999
USD

 

Abstract

Traditional game playing programs have relied on advanced search algorithms and hand-tuned evaluation functions to play 'intelligently'. A historical overview of these techniques is provided, followed by a revealing look at recent developments in coevolutionary strategies to facilitate game learning. The use of particle swarms in conjunction with neural networks to learn how to play tic-tac-toe is experimentally compared to current game learning research. The use of a new particle swarm neighbourhood structure and innovative board state representation show promising results that warrant further investigation to its application in more complex games like checkers.

Loading full text...

Full text loading...

Loading

Article metrics loading...

/content/comp/2004/32/EJC27960
2004-06-01
2017-05-22

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error