A simple heuristic search method for the automatic generation of neural-based game artificial intelligence architectures in Ms. Pac-man

Tse , Guan Tan and Teo, Jason Tze Wi and Patricia Anthony, (2010) A simple heuristic search method for the automatic generation of neural-based game artificial intelligence architectures in Ms. Pac-man. In: 10th International Conference on Information Sciences, Signal Processing and their Applications (ISSPA 2010), 10-13 May 2010, Kuala Lumpur, Malaysia.

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Official URL: http://dx.doi.org/10.1109/ISSPA.2010.5605407

Abstract

In this work, we develop a game controller called HillClimbingNet (Hill-Climbing Neural Network) for playing Ms. Pac-man that combines the hill-climbing concept and simple feedforward neural network. The computational experiments have been conducted to evaluate and compare the proposed algorithm against Random Direction (RandDir) and Random Neural Network (RandNet) systems. According to the simulation results, HillClimbingNet has achieved an average score of 6290, but only 439 and 735 on the RandDir and RandNet, respectively. HillClimbingNet has a very good performance. © 2010 IEEE.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Feedforward neural networks, Games, Intelligent systems, Search methods, Unsupervised learning
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:2162
Deposited By:IR Admin
Deposited On:10 Mar 2011 13:05
Last Modified:29 Dec 2014 16:11

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