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Journal of Computer Science and Technology

, Volume 27, Issue 5, pp 996–1006 | Cite as

Effect of Look-Ahead Depth in Evolutionary Checkers

Regular Paper

Abstract

It is intuitive that allowing a deeper search into a game tree will result in a superior player to one that is restricted in the depth of the search that it is allowed to make. Of course, searching deeper into the tree comes at increased computational cost and this is one of the trade-offs that has to be considered in developing a tree-based search algorithm. There has been some discussion as to whether the evaluation function, or the depth of the search, is the main contributory factor in the performance of an evolved checkers player. Some previous research has investigated this question (on Chess and Othello), with differing conclusions. This suggests that different games have different emphases, with respect to these two factors. This paper provides the evidence for evolutionary checkers, and shows that the look-ahead depth (like Chess, perhaps unsurprisingly) is important. This is the first time that such an intensive study has been carried out for evolutionary checkers and given the evidence provided for Chess and Othello this is an important study that provides the evidence for another game. We arrived at our conclusion by evolving various checkers players at different ply depths and by playing them against one another, again at different ply depths. This was combined with the two-move ballot (enabling more games against the evolved players to take place) which provides strong evidence that depth of the look-ahead is important for evolved checkers players.

Keywords

evolutionary Checkers look-ahead depth neural network 

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Copyright information

© Springer Science+Business Media New York & Science Press, China 2012

Authors and Affiliations

  1. 1.College of ComputerAl-Anbar UniversityRamadiIraq
  2. 2.School of Computer ScienceThe University of NottinghamNottinghamU.K.

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