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Coevolving game-playing agents: Measuring performance and intransitivities

Samothrakis, S and Lucas, S and Runarsson, TP and Robles, D (2013) 'Coevolving game-playing agents: Measuring performance and intransitivities.' IEEE Transactions on Evolutionary Computation, 17 (2). 213 - 226. ISSN 1089-778X

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Abstract

Coevolution is a natural choice for learning in problem domains where one agent's behavior is directly related to the behavior of other agents. However, there is a known tendency for coevolution to produce mediocre solutions. One of the main reasons for this is cycling, caused by intransitivities among a set of players. In this paper, we explore the link between coevolution and games, and revisit some of the coevolutionary literature in a games and measurement context. We propose a set of measurements to identify cycling in a population and a new algorithm that tries to minimize cycling in strictly competitive (zero sum) games. We experimentally verify our approach by evolving weighted piece counter value functions to play othello, a classic two-player perfect information board game. Our method is able to find extremely strong value functions of this type. © 1997-2012 IEEE.

Item Type: Article
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: 19 Oct 2012 22:22
Last Modified: 30 Jan 2019 16:17
URI: http://repository.essex.ac.uk/id/eprint/4121

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