[Amigoni, F., Basilico, N. and Gatti, N. (2009). Finding the optimal strategies for robotic patrolling with adversaries in topologically-represented environments, Proceedings of the 26th International Conference on Robotics and Automation (ICRA’09), Kobe, Japan, pp. 819-824.]Search in Google Scholar
[Cichosz, P. and Pawełczak, Ł. (2014). Imitation learning of car driving skills with decision trees and random forests, International Journal of Applied Mathematics and Computer Science 24(3): 579-597, DOI: 10.2478/amcs-2014-0042.10.2478/amcs-2014-0042]Search in Google Scholar
[Conitzer, V. and Sandholm, T. (2006). Computing the optimal strategy to commit to, Proceedings of the 7th ACM Conference on Electronic Commerce, EC’06, Ann Arbor, MI, USA, pp. 82-90.]Search in Google Scholar
[Kott, A. and McEneany, W.M. (2007). Adversarial Reasoning: Computational Approaches to Reading the Opponents Mind, Chapman and Hall/CRC, Boca Raton, FL.10.1201/9781420011012]Search in Google Scholar
[McLennan, A. and Tourky, R. (2006). From imitation games to Kakutani, http://cupid.economics.uq.edu.au/mclennan/Papers/kakutani60.pdf, (unpublished).]Search in Google Scholar
[McLennan, A. and Tourky, R. (2010a). Imitation games and computation, Games and Economic Behavior 70(1): 4-11.10.1016/j.geb.2009.08.003]Search in Google Scholar
[McLennan, A. and Tourky, R. (2010b). Simple complexity from imitation games, Games and Economic Behavior 68(2): 683-688.10.1016/j.geb.2009.10.003]Search in Google Scholar
[Osborne, M. and Rubinstein, A. (1994). A Course in Game Theory, MIT Press, Cambridge, MA.]Search in Google Scholar
[Paruchuri, P., Pearce, J.P. and Kraus, S. (2008). Playing games for security: An efficient exact algorithm for solving Bayesian Stackelberg games, Proceedings of the 7th International Conference on Autonomous Agents and Multi-Agent Systems (AAMAS’08), Estoril, Portugal, pp. 895-902.]Search in Google Scholar
[Pelta, D. and Yager, R. (2009). On the conflict between inducing confusion and attaining payoff in adversarial decision making, Information Sciences 179(1-2): 33-40.10.1016/j.ins.2008.08.023]Search in Google Scholar
[Price, K., Storn, R. and Lampinen, J. (2005). Differential Evolution: A Practical Approach to Global Optimization, Natural Computing Series, Springer-Verlag New York, Inc., Syracuse, NJ.]Search in Google Scholar
[Qin, A.K., Huang, V.L. and Suganthan, P.N. (2009). Differential evolution: Algorithm with strategy adaptation for global numerical optimization, IEEE Transactions on Evolutionary Computation 13(2): 398-417.10.1109/TEVC.2008.927706]Search in Google Scholar
[Storn, R. and Price, K. (1997). Differential evolution: A simple and efficient heuristic for global optimization over continuous spaces, Journal of Global Optimization 11(10): 341-359.10.1023/A:1008202821328]Search in Google Scholar
[Tambe, M. (2012). Security and Game Theory: Algorithms, Deployed Systems, Lessons Learned, Cambridge University Press, New York, NY.10.1109/Allerton.2012.6483443]Search in Google Scholar
[Thagard, P. (1992). Adversarial problem solving: Modeling an opponent using explanatory coherence, Cognitive Science 16(1): 123-149.10.1207/s15516709cog1601_4]Search in Google Scholar
[Triguero, I., Garcia, S. and Herrera, F. (2011). Differential evolution for optimizing the positioning of prototypes in nearest neighbor classification, Pattern Recognition 44(4): 901-916.10.1016/j.patcog.2010.10.020]Search in Google Scholar
[Villacorta, P.J. and Pelta, D.A. (2012). Theoretical analysis of expected payoff in an adversarial domain, Information Sciences 186(4): 93-104.10.1016/j.ins.2011.09.031]Search in Google Scholar
[Villacorta, P.J., Pelta, D.A. and Lamata, M.T. (2013). Forgetting as a way to avoid deception in a repeated imitation game, Autonomous Agents and Multi-Agent Systems 27(3): 329-354.10.1007/s10458-012-9205-x]Search in Google Scholar
[Villacorta, P. and Pelta, D. (2011). Expected payoff analysis of dynamic mixed strategies in an adversarial domain, Proceedings of the 2011 IEEE Symposium on Intelligent Agents (IA 2011), Paris, France, pp. 116-122. ]Search in Google Scholar