Uniform versus Gaussian mutators in automatic generation of game AI in Ms. Pac-Man using hill-climbing

Tse, Guan Tan and Teo, Jason Tze Wi and Patricia Anthony, (2010) Uniform versus Gaussian mutators in automatic generation of game AI in Ms. Pac-Man using hill-climbing. In: International Conference on Information Retrieval and Knowledge Management : Exploring the Invisible World (CAMP'10), 17-18 March 2010, Shah Alam, Selangor, Malaysia.

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Abstract

This paper explores the idea of combining the hillclimbing concept into feed-forward artificial neural networks (ANN) to develop intelligent controllers to play the Ms. Pacman game. The resulting algorithm is referred to as the HillClimbingNet. A comparison with a random system, called RandNet is conducted on the same problem. We also present a survey of the effects of two most popular probability density functions, uniform and Gaussian distributions/mutators on the introduced algorithm. The results clearly indicate the strong potential of the hill-climbing strategy as a direct search method in tandem with a Gaussian-based mutator to optimize the ANN for playing Ms. Pac-Man. ©2010 IEEE.

Item Type: Conference or Workshop Item (UNSPECIFIED)
Uncontrolled Keywords: Automatic Generation, Direct search methods, Feed-forward artificial neural networks, Gaussians, Hill climbing; Intelligent controllers, Random systems
Subjects: Q Science > QA Mathematics > QA76 Computer software
Divisions: SCHOOL > School of Engineering and Information Technology
Depositing User: Unnamed user with email storage.bpmlib@ums.edu.my
Date Deposited: 07 Mar 2011 00:43
Last Modified: 29 Dec 2014 08:09
URI: http://eprints.ums.edu.my/id/eprint/2049

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