Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/61144
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Type: Book chapter
Title: Adapting to human gamers using coevolution
Author: Avery, P.
Michalewicz, Z.
Citation: Advances in Machine Learning II, 2010 / Koronacki, J. (ed./s), pp.75-100
Publisher: Springer
Publisher Place: Germany
Issue Date: 2010
Series/Report no.: Studies in Computational Intelligence
ISBN: 9783642051784
Statement of
Responsibility: 
Phillipa M. Avery and Zbigniew Michalewicz
Abstract: No matter how good a computer player is, given enough time human players may learn to adapt to the strategy used, and routinely defeat the computer player. A challenging task is to mimic this human ability to adapt, and create a computer player that can adapt to its opposition’s strategy. By having an adaptive strategy for a computer player, the challenge it provides is ongoing. Additionally, a computer player that adapts specifically to an individual human provides a more personal and tailored game play experience. To address this need we have investigated the creation of such a computer player. By creating a computer player that changes its strategy with influence from the human strategy, we have shown that the holy grail of gaming – an individually tailored gaming experience, is indeed possible. We designed the computer player for the game of TEMPO, a zero sum military planning game. The player was created through a process that reverse engineers the human strategy and uses it to coevolve the computer player.
Rights: © Springer-Verlag Berlin Heidelberg 2010
RMID: 0020100137
DOI: 10.1007/978-3-642-05179-1_4
Published version: https://doi.org/10.1007/978-3-642-05179-1
Appears in Collections:Computer Science publications

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