Opponent modelling for case-based adaptive game AI》.pdfVIP

Entertainment Computing 1 (2009) 27–37 Contents lists available at ScienceDirect Entertainment Computing journal homepage: /entcom Opponent modelling for case-based adaptive game AI Sander C.J. Bakkes *, Pieter H.M. Spronck, H. Jaap van den Herik Tilburg centre for Creative Computing (TiCC), Tilburg University, P.O. Box 90153, 5000 LE Tilburg, The Netherlands a r t i c l e i n f o a b s t r a c t Article history: In previous work we introduced a novel approach to adaptive game AI that was focussed on the rapid and Received 9 July 2009 reliable adaptation to game circumstances. We named the approach ‘case-based adaptive game AI’. In the Revised 2 September 2009 approach, domain knowledge required to adapt to game circumstances is gathered automatically by the Accepted 10 September 2009 game AI, and is exploited immediately (i.e., without trials and without resource-intensive learning) to evoke effective behaviour in a controlled manner in online play. In the research discussed in this article we investigate to what extent incorporating opponent modelling enhances the performance of case-based Keywords: adaptive game AI. In our approach, models of the opponent players are generated automatically, on the Game AI basis of observations drawn from a multitude of games. We performed experiments