An adaptation of social Learning in evolutionary computation for tic-tac-toe.

This paper investigates an integration of individual and social learning, utilising evolutionary neural networks, in order to evolve game playing strategies. Individual learning enables players to create their own strategies. Then, we allow the use of social learning to allow poor performing players...

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Main Authors: Yaakob, Razali, Kendall, Graham
Format: Article
Language:English
English
Published: 2009
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/13005/
http://psasir.upm.edu.my/id/eprint/13005/1/An%20adaptation%20of%20social%20Learning%20in%20evolutionary%20computation%20for%20tic.pdf
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author Yaakob, Razali
Kendall, Graham
author_facet Yaakob, Razali
Kendall, Graham
author_sort Yaakob, Razali
building UPM Institutional Repository
collection Online Access
description This paper investigates an integration of individual and social learning, utilising evolutionary neural networks, in order to evolve game playing strategies. Individual learning enables players to create their own strategies. Then, we allow the use of social learning to allow poor performing players to learn from players which are playing at a higher level. The feed forward neural networks are evolved via evolution strategies. The evolved neural network players play first and compete against a nearly perfect player. At the end of each game, the evolved players receive a score based on whether they won, lost or drew. Our results demonstrate that the use of social learning helps players learn strategies, which are superior to those evolved when social learning is not utilised.
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English
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spelling upm-130052015-11-03T01:51:27Z http://psasir.upm.edu.my/id/eprint/13005/ An adaptation of social Learning in evolutionary computation for tic-tac-toe. Yaakob, Razali Kendall, Graham This paper investigates an integration of individual and social learning, utilising evolutionary neural networks, in order to evolve game playing strategies. Individual learning enables players to create their own strategies. Then, we allow the use of social learning to allow poor performing players to learn from players which are playing at a higher level. The feed forward neural networks are evolved via evolution strategies. The evolved neural network players play first and compete against a nearly perfect player. At the end of each game, the evolved players receive a score based on whether they won, lost or drew. Our results demonstrate that the use of social learning helps players learn strategies, which are superior to those evolved when social learning is not utilised. 2009-09 Article PeerReviewed application/pdf en http://psasir.upm.edu.my/id/eprint/13005/1/An%20adaptation%20of%20social%20Learning%20in%20evolutionary%20computation%20for%20tic.pdf Yaakob, Razali and Kendall, Graham (2009) An adaptation of social Learning in evolutionary computation for tic-tac-toe. International Journal of Computer Science and Network Security, 9 (9). pp. 294-300. ISSN 1738-7906 Neural networks (Computer science). Evolutionary programming (Computer science). Evolutionary computation. English
spellingShingle Neural networks (Computer science).
Evolutionary programming (Computer science).
Evolutionary computation.
Yaakob, Razali
Kendall, Graham
An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title_full An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title_fullStr An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title_full_unstemmed An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title_short An adaptation of social Learning in evolutionary computation for tic-tac-toe.
title_sort adaptation of social learning in evolutionary computation for tic-tac-toe.
topic Neural networks (Computer science).
Evolutionary programming (Computer science).
Evolutionary computation.
url http://psasir.upm.edu.my/id/eprint/13005/
http://psasir.upm.edu.my/id/eprint/13005/1/An%20adaptation%20of%20social%20Learning%20in%20evolutionary%20computation%20for%20tic.pdf