Coevolving strategic intelligence

Strategic decision making done in parallel with the opposition makes it difficult to predict the oppositionpsilas strategy. An important aspect in deciding a move is evaluating your opponentpsilas past moves and using them to predict future movement. In the game of TEMPO this is done through the purchase of intelligence, which gives you a relative view of your opponentpsilas choices. The research presented here seeks to evaluate the way this intelligence is used in the current game, and present an alternative method of representation. This alternate mechanism is then used in a co evolutionary system to obtain a computer player that will self-learn the importance of using opposition data in strategic decision making.

[1]  Zbigniew Michalewicz,et al.  Short and long term memory in coevolution , 2008 .

[2]  C. Miles Co-evolving Real-Time Strategy Game Playing Influence Map Trees With Genetic Algorithms , 2022 .

[3]  Zbigniew Michalewicz,et al.  Static experts and dynamic enemies in coevolutionary games , 2007, 2007 IEEE Congress on Evolutionary Computation.

[4]  Sushil J. Louis,et al.  Combining Case-Based Memory with Genetic Algorithm Search for Competent Game AI , 2005, ICCBR Workshops.

[5]  Ciência política,et al.  Chairman of the Joint Chiefs of Staff , 2010 .

[6]  Michael Buro,et al.  RTS Games and Real-Time AI Research , 2003 .

[7]  Zbigniew Michalewicz,et al.  Coevolutionary TEMPO game , 2004, Proceedings of the 2004 Congress on Evolutionary Computation (IEEE Cat. No.04TH8753).

[8]  Sushil J. Louis,et al.  Playing to learn: case-injected genetic algorithms for learning to play computer games , 2005, IEEE Transactions on Evolutionary Computation.

[9]  Zbigniew Michalewicz,et al.  Coevolutionary optimization of fuzzy logic intelligence for strategic decision support , 2005, IEEE Transactions on Evolutionary Computation.

[10]  Zbigniew Michalewicz,et al.  A Historical Population in a Coevolutionary System , 2007, 2007 IEEE Symposium on Computational Intelligence and Games.

[11]  Dr. Zbigniew Michalewicz,et al.  How to Solve It: Modern Heuristics , 2004 .