Game AI generation using evolutionary multi-objective optimization

Tong, Chang Kee and Chin, Kim On and Teo, Jason Tze Wi and Mountstephens, James (2012) Game AI generation using evolutionary multi-objective optimization. In: 2012 IEEE Congress on Evolutionary Computation, CEC 2012, 10-15 June 2012, Brisbane, Australia.

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Official URL: http://dx.doi.org/ 10.1109/CEC.2012.6256638

Abstract

This paper presents the design and evaluation of a full AI controller for Real-Time Strategy (RTS) games using techniques from Evolutionary Computing (EC). The design is novel in its use of a modified Pareto Differential Evolution (PDE) algorithm for bi-objective optimization of the weights of an Artificial Neural Network (ANN) controller when only single-objective optimization has so far been studied. The two main aims of this research are to: (1) develop controllers capable of defeating opponents of varying difficulty levels, which may assist in commercial RTS AI development, and (2) minimize the number of neurons used in the ANN architecture, an issue primarily of efficiency. Experimental results using the popular Warcraft III platform demonstrate success with both aims: the optimized controller was able to win any battle using only a minimal number of hidden neurons, but sub-optimal controllers were able to provide opponents of any intermediate difficulty.

Item Type:Conference Paper (UNSPECIFIED)
Uncontrolled Keywords:Artificial Intelligence (AI), Artificial Neural Networks (ANN), Evolutionary Multi-Objective Optimization (EMO), Pareto Differential Evolution (PDE), Real-Time Strategy Game (RTS), Warcraft III, Bi-objective optimization, Evolutionary computing, Evolutionary multiobjective optimization, Hidden neurons, Pareto differential evolutions, Real-time strategy games, Single objective optimization, Suboptimal controllers, Warcraft III, Evolutionary algorithms, Multiobjective optimization, Neural networks, Real time systems, Computer software
Subjects:?? QA75.5-76.95 ??
Divisions:SCHOOL > School of Engineering and Information Technology
ID Code:5323
Deposited By:IR Admin
Deposited On:05 Nov 2012 15:24
Last Modified:08 Sep 2014 12:45

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