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Neural network application for automatic decisions in poker

Wybrane pełne teksty z tego czasopisma
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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The paper describes a system taking automatic decisions in Poker Texas Hold'em. It can play the game autonomously, so we will refer to it as a bot. Apart from various poker evaluations and decision taking methods, the bot uses a neural network to asses future movements of opponents. A few latest solutions in a field of automatic decisions in conflict situations are also summarised.
Rocznik
Strony
119--127
Opis fizyczny
Bibliogr. 17 poz.
Twórcy
autor
autor
autor
  • AGH University of Science and Technology, Department of Electronics, Department of Computer Science al. Mickiewicza 30, Kraków, bziolko@agh.edu.pl
Bibliografia
  • [1] Baba, N., Jain, L. C., and (eds.), H. H., Advanced Intelligent Paradigms in Computer Games, Springer, 2007.
  • [2] (Ed.), S. C. R., AI game programming wisdom, Charles River Media, Inc., 2002.
  • [3] Funge, J., Artificial Intelligence for Computer Games: An Introduction, A K Peters, Wellesley, MA., 2004.
  • [4] Millington, I. and Funge, J., Artificial intelligence for games, Elsevier, 2009.
  • [5] Billings, D., Davidson, A., Schaeffer, J., and Szafron, D., The Challenge of Poker, Artificial Intelligence Journal, 2001.
  • [6] Billings, D., Burch, N., Davidson, A., Holte, R., Schaeffer, J., Schauenberg, T., and Szafron, D., Approximating Game-Theoretic Optimal Strategies for Full-scale Poker, Proceedings of the 2003 International Joint Conference on Artificial Intelligence (IJCAI-03), 2003.
  • [7] Billings, D., Davidson, A., Schauenberg, T., Burch, N., Bowling, M., Holte, R., Schaeffer, J., and Szafron, D., Game-Tree Search with Adaptation in Stochastic Imperfect-Information Games, Lecture Notes in Computer Science, Vol. 3846, 2006, pp. 21 - 34.
  • [8] Davidson, A., Billings, D., Schaeffer, J., and Szafron, D., Improved Opponent Modeling in Poker, Proceedings of International Conference on Artificial Intelligence (ICAI'2000), pp. 1467-1473.
  • [9] Davidson, A., Opponent Modeling in Poker: Learning and Acting in a Hostile Environment, MSc. Thesis, University of Alberta.
  • [10] Ahn, B. and Choi, S., Conflict resolution in a knowledge-based system using multiple attribute decision-making, Expert Systems with Applications, Vol. 36, 2009, pp. 11552-11558.
  • [11] Liu, S., Wang, J., and Lin, H., Associated-Conflict Analysis Using Covering Based on Granular Computing, Lecture Notes in Computer Science, Vol. 6328, 2010, pp. 297-303.
  • [12] Cox, L., Game Theory and Risk Analysis, Risk Analysis, Vol. 29, No. 8, 2009, pp. 1062-1068.
  • [13] Al-Shawa, M. and Basir, O., Constrained Rationality: Formal Goals- Reasoning Approach to Strategic Decision & Conflict Analysis, Proceedings of 2009 IEEE International Conference on Systems, Man and Cybernetics, 2009, pp. 1439-1445.
  • [14] Karunatillake, N. C., Jennings, N. R., Rahwan, I., and McBurney, P., Dialogue Games that Agents Play within a Society, Artificial Intelligence, Vol. 173, 2009, pp. 935-981.
  • [15] Bashar, M., Hipel, K., and Kilgour, D., Fuzzy Preferences in Conflict Resolution, Proceedings of 2009 IEEE International Conference on Systems, Man and Cybernetics, 2009, pp. 2332-2337.
  • [16] Sklansky, D. and Malmuth, M., Texas Hold'em for the Advanced Player, Two Plus Two Publishing, 1994.
  • [17] Tadeusiewicz, R., Sieci neuronowe, Akademicka Oficyna Wydawnicza, Warszawa, 1993.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-LOD7-0032-0067
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