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Generating diverse opponents with multiobjective evolution

Agapitos, A and Togelius, J and Lucas, SM and Schmidhuber, J and Konstantinidis, A (2008) Generating diverse opponents with multiobjective evolution. In: UNSPECIFIED, ? - ?.

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For computational intelligence to be useful in creating game agent AI, we need to focus on creating interesting and believable agents rather than just learn to play the games well. To this end, we propose a way use multiobjective evolutionary algorithms to automatically create populations of Non-Player Characters (NPCs), such as opponents and collaborators that are interestingly diverse in behaviour space. Experiments 'are presented where a number of partially conflicting objectives are defined for racing game competitors, and multiobjective evolution of Genetic Programming-based controllers yield pareto fronts of interesting controllers. ©2008 IEEE.

Item Type: Conference or Workshop Item (Paper)
Additional Information: Published proceedings: 2008 IEEE Symposium on Computational Intelligence and Games, CIG 2008
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Science and Health > Computer Science and Electronic Engineering, School of
Depositing User: Jim Jamieson
Date Deposited: 03 Oct 2012 09:16
Last Modified: 23 Jan 2019 02:15

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