Please use this identifier to cite or link to this item:
|Scopus||Web of Science®||Altmetric|
|Title:||Adapting to human gamers using coevolution|
|Citation:||Advances in Machine Learning II, 2010 / Koronacki, J. (ed./s), pp.75-100|
|Series/Report no.:||Studies in Computational Intelligence|
|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|
|Appears in Collections:||Computer Science publications|
Files in This Item:
There are no files associated with this item.
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.