Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/61144
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dc.contributor.authorAvery, P.-
dc.contributor.authorMichalewicz, Z.-
dc.contributor.editorKoronacki, J.-
dc.date.issued2010-
dc.identifier.citationAdvances in Machine Learning II, 2010 / Koronacki, J. (ed./s), vol.263, pp.75-100-
dc.identifier.isbn9783642051784-
dc.identifier.urihttp://hdl.handle.net/2440/61144-
dc.description.abstractNo 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.-
dc.description.statementofresponsibilityPhillipa M. Avery and Zbigniew Michalewicz-
dc.language.isoen-
dc.publisherSpringer-
dc.relation.ispartofseriesStudies in Computational Intelligence-
dc.rights© Springer-Verlag Berlin Heidelberg 2010-
dc.source.urihttp://dx.doi.org/10.1007/978-3-642-05179-1_4-
dc.titleAdapting to human gamers using coevolution-
dc.typeBook chapter-
dc.identifier.doi10.1007/978-3-642-05179-1_4-
dc.publisher.placeGermany-
pubs.publication-statusPublished-
Appears in Collections:Aurora harvest
Computer Science publications

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