B. H. Cho, S. H. Jung, Y. R. Seong, and H. R. Oh, Exploiting Intelligence in Fighting Action Games Using Neural Networks, IEICE Transactions on Information and Systems, vol.89, issue.3, pp.1249-1256, 2006.
DOI : 10.1093/ietisy/e89-d.3.1249

B. H. Cho, C. Park, and K. Yang, Comparison of AI Techniques for Fighting Action Games -Genetic Algorithms, Neural Networks/Evolutionary Neural Networks. In: Entertainment Computing -ICEC 2007, 2007.

B. Cho, S. Jung, K. H. Shim, Y. Seong, and H. Oh, Reinforcement Learning of Intelligent Characters in Fighting Action Games, Lecture Notes in Computer Science, vol.4, issue.2, pp.310-313, 2006.
DOI : 10.1007/11596448_159

T. Graepel, R. Herbrich, and J. Gold, Learning to fight, Proceedings of the International Conference on Computer Games: Artificial Intelligence, Design and Education, pp.193-200, 2004.

F. Lu, K. Yamamoto, L. Nomura, S. Mizuno, Y. Lee et al., Fighting game artificial intelligence competition platform, 2013 IEEE 2nd Global Conference on Consumer Electronics (GCCE), pp.320-323, 2013.
DOI : 10.1109/GCCE.2013.6664844

S. Lueangrueangroj and V. Kotrajaras, Real-time imitation based learning for commercial fighting games, Computer Games, Multimedia and Allied Technology (CGAT), 2nd Annual International Conference on, pp.1-3, 2009.
DOI : 10.1037/e602482011-002

S. Osaka, R. Thawonmas, and T. Shibazaki, Investigation of Various Online Adaptation Methods of Computer-Game AI Rulebase in Dynamic Scripting, Proceedings of the 1st International Conference on Digital Interactive Media Entertainment and Arts (DIME-ARTS 2006), 2006.

H. Park and K. J. Kim, Learning to play fighting game using massive play data, Computational Intelligence and Games (CIG), 2014 IEEE Conference on, pp.1-2, 2014.

M. Ponsen, P. Spronck, M. Avila, H. Aha, and D. W. , Knowledge acquisition for adaptive game AI, Science of Computer Programming, vol.67, issue.1, pp.59-75, 2007.
DOI : 10.1016/j.scico.2007.01.006

URL : https://doi.org/10.1016/j.scico.2007.01.006

A. Ricciardi and P. Thill, Adaptive AI for fighting games, pp.2015-2017, 2008.

S. Saini, C. Dawson, and P. Chung, Mimicking player strategies in fighting games, 2011 IEEE International Games Innovation Conference (IGIC), pp.44-47, 2011.
DOI : 10.1109/IGIC.2011.6115128

P. Spronck, M. Ponsen, I. Sprinkhuizen-kuyper, and E. Postma, Adaptive game AI with dynamic scripting, Machine Learning, vol.63, issue.3, pp.217-248, 2006.
DOI : 10.1007/s10994-006-6205-6

URL : https://link.springer.com/content/pdf/10.1007%2Fs10994-006-6205-6.pdf

I. Szita, M. Ponsen, and P. Spronck, Effective and Diverse Adaptive Game AI. Computational Intelligence and AI in Games, IEEE Transactions on, vol.1, issue.1, pp.16-27, 2009.
DOI : 10.1109/tciaig.2009.2018706

URL : http://ticc.uvt.nl/~pspronck/pubs/SzitaPonsenSpronck.pdf

R. Thawonmas and S. Osaka, A method for online adaptation of computer-game AI rulebase, Proceedings of the 2006 ACM SIGCHI international conference on Advances in computer entertainment technology , ACE '06, 2006.
DOI : 10.1145/1178823.1178843

W. Thunputtarakul and V. Kotrajaras, Data Analysis for Ghost AI Creation in Commercial Fighting Games, pp.37-41, 2007.

T. Timuri, P. Spronck, and H. J. Van-den-herik, Automatic Rule Ordering for Dynamic Scripting, 2007 AAAI Conference on, pp.49-54, 2007.

K. Yamamoto, S. Mizuno, C. Y. Chu, and R. Thawonmas, Deduction of fighting-game countermeasures using the k-nearest neighbor algorithm and a game simulator, 2014 IEEE Conference on Computational Intelligence and Games, pp.1-5, 2014.
DOI : 10.1109/CIG.2014.6932915