Chapter

Advances in Machine Learning II

Volume 263 of the series Studies in Computational Intelligence pp 75-100

Adapting to Human Gamers Using Coevolution

  • Phillipa M. AveryAffiliated withDepartment of Computer Science, University of Adelaide
  • , Zbigniew MichalewiczAffiliated withSchool of Computer Science, University of Adelaide, South Australia; also at the Institute of Computer Science, Polish Academy of SciencesPolish-Japanese Institute of Information Technology

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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.