Tse, Guan Tan and Teo, Jason and Anthony, Patricia (2010) Evolution strategies for evolving artificial neural networks in an arcade game. In: Knowledge Management International Conference 2010 (KMICe2010), 25-27 May 2010, Kuala Terengganu, Malaysia.

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Abstract

The aim of this paper is to use a simple but powerful evolutionary algorithm called Evolution Strategies (ES) to evolve the connection weights and biases of feed-forward artificial neural networks (ANN) and to examine its learning ability through computational experiments in a non-deterministic and dynamic environment, which is the well-known arcade game called Ms. Pac-man.The resulting algorithm is referred to as an Evolution Strategies Neural Network or ESNet.This study is an attempt to create an autonomous intelligent controller to play the game.The comparison of ESNet with two random systems, Random Direction (RandDir) and Random Neural Network (RandNet) yields promising results.

Item Type:	Conference or Workshop Item (Paper)
Additional Information:	ISBN 978-983-2078-40-1 Organized by: UUM College of Art & Sciences, Universiti Utara Malaysia
Uncontrolled Keywords:	Evolution Strategies, Evolutionary Artificial Neural Networks, Ms. Pac-man
Subjects:	Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:	College of Arts and Sciences
Depositing User:	Mrs. Norazmilah Yaakub
Date Deposited:	05 Jun 2014 01:26
Last Modified:	05 Jun 2014 01:26
URI:	https://repo.uum.edu.my/id/eprint/11255

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