1887

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

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

Article metrics loading...

/content/comp/2004/32/EJC27960
2004-06-01
2016-12-05
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