Designing high-level decision making systems based on fuzzy if–then rules for a point-to-point car racing game

• Agapitos A, Togelius J, Lucas SM (2007) Evolving controllers for simulated car racing using object oriented genetic programming. In: Proceedings of the 9th annual conference on Genetic and evolutionary computation. ACM, London, pp 1543–1550

• Araki N, Yoshida K, Tsuruoka Y, Tsujii J (2007) Move prediction in go with the maximum entropy method. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 189–195

• Ashlock DA (2007) Cooperation in prisoner’s dilemma on graphs. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 48–55

• Chen W-Y, Payandeh S (2007) Micro robot hockey simulator—game engine design. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 9–16

• DeLooze LL, Downey J (2007) Bridge bidding with imperfect information. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 368–373

• Ghoneim A, Abbass H, Barlow M (2007) Information sharing in the iterated prisoner’s dilemma game. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 56–62

• Ishibuchi H, Nozaki K, Tanaka H (1992) Distributed representation of fuzzy rules and its application to pattern classification. Fuzzy Sets Syst 52:21–32

  Article  Google Scholar 

• Kim K-J, Choi H, Cho S-B (2007) Hybrid of evolution and reinforcement learning for othello players. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 203–209

• Leigh R, Louis SJ, Miles C (2007) Using a genetic algorithm to explore a*-like pathfinding algorithms. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 72–79

• Marques H, Togelius J, Kogutowska M, Holland O, Lucas SM (2007) Sensorless but not senseless: prediction in evolutionary car racing. In: Artificial life, 2007. ALIFE ’07. IEEE Symposium on, pp 370–377

• Mayer HA (2007) Board representations for neural go players learning by temporal difference. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 183–188

• McFarlin DS, Todd PM (2007) Evolving a better adversary: a case study in a german castle. In: Artificial life, 2007. ALIFE ’07. IEEE Symposium on, pp 229–235

• Miles C, Quiroz J, Leigh R, Louis SJ (2007) Co-evolving influence map tree based strategy game players. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 88–95

• Nakashima T, Udo M, Ishibuchi H (2003a) A fuzzy reinforcement learning for a ball interception problem. Pages in CD–ROM (8 pages), Padova, Italy

• Nakashima T, Udo M, Ishibuchi H (2003b) Implementation of fuzzy q-learning for a soccer agent, St. Louis, USA, pp 533–536

• Nakashima T, Takatani M, Udo M, Ishibuchi H (2004) An evolutionary approach for strategy learning in robocup soccer, Den Hague, Netherlands, pp 2023–2028

• Nakashima T, Takatani M, Udo M, Ishibuchi H, Nii M (2005) Performance evaluation of an evolutionary method for robocup soccer strategies. Pages in CR–ROM (8 pages), Osaka, Japan

• Nakashima T, Takatani M, Ishibuchi H, Nii M (2006) The effect of using match history on the evolution of robocup soccer team strategies, Reno/Lake Tahoe, Nevada, USA, pp 60–66

• Newborn M, Newborn M (1996) Kasparov versus deep blue: computer chess comes of age. Springer, New York

• Nozaki K, Ishibuchi H, Tanaka H (1996) Adaptive fuzzy rule-based classification systems. IEEE Trans Fuzzy Syst 4:238–250

  Article  Google Scholar 

• Quek H-Y, Goh CK (2007) Adaptation of iterated prisoner’s dilemma strategies by evolution and learning. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 40–47

• Riedmiller M, Gabel T (2007) On experiences in a complex and competitive gaming domain: reinforcement learning meets robocup. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 17–23

• Runarsson TP, Jonsson EO (2007) Effect of look-ahead search depth in learning position evaluation functions for othello using greedy exploration. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 210–215

• Togelius J (2004) Evolution of a subsumption architecture neurocontroller. J Intell Fuzzy Syst 15:15–20

  Google Scholar 

• Togelius J (2007) Optimization, lmitation and innovation: computational intelligence and games. PhD thesis, Department of Computer Science, University of Essex

• Togelius J, Lucas SM (2006) Evolving robust and specialized car racing skills. In: Evolutionary computation, 2006. CEC 2006. IEEE Congress on, pp 1187–1194

• Togelius J, Nardi RD, Lucas SM (2006) Making racing fun through player modeling and track evolution. In: SAB workshop on adaptive approaches to optimizing player satisfaction

• Togelius J, Lucas SM, Nardi RD (2007a) Computational intelligence in racing games. Studies in computational intelligence, vol 71. Springer, Berlin, pp 39–69

• Togelius J, De Nardi R, Lucas SM (2007b) Towards automatic personalised content creation for racing games. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 252–259

• Vicenç Torra (2002) A review of the construction of hierarchical fuzzy systems. Int J Intell Syst 17(5):531–543

  Article  MATH  MathSciNet  Google Scholar 

• Wang Y, Gelly S (2007) Modifications of uct and sequence-like simulations for monte-carlo go. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 175–182

• Wittkamp M, Barone L, While L (2007) A comparison of genetic programming and look-up table learning for the game of spoof. In: Computational intelligence and games, 2007. CIG 2007. IEEE Symposium on, pp 63–71

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