-
1
-
-
70449560435
-
Game player strategy pattern recognition and how UCT algorithms apply pre-knowledge of player's strategy to improve opponent AI
-
Indexed by EI Compendex
-
Suoju He, Yi Wang, Fan Xie, Jin Meng, Hongtao Chen, Sai Luo, Zhiqing Liu, Qiliang Zhu. Game Player Strategy Pattern Recognition and How UCT Algorithms Apply Pre-Knowledge of Player's Strategy to Improve Opponent AI. In Proceedings of International Conference on Innovation in Software Engineering (ISE'2008). Indexed by EI Compendex.
-
Proceedings of International Conference on Innovation in Software Engineering (ISE'2008)
-
-
He, S.1
Wang, Y.2
Xie, F.3
Meng, J.4
Chen, H.5
Luo, S.6
Liu, Z.7
Zhu, Q.8
-
3
-
-
78149301353
-
-
retrieved on 08/18/09
-
http://www.gameontology.org/index.php/Dynamic-Difficulty-Adjustment, retrieved on 08/18/09.
-
-
-
-
4
-
-
32144439231
-
AI for dynamic difficulty adjustment in games
-
San Jose
-
Hunicke, R., and Chapman, V., "AI for Dynamic Difficulty Adjustment in Games". Challenges in Game Artificial Intelligence AAAI Workshop, San Jose, 2004, pp. 91-96.
-
(2004)
Challenges in Game Artificial Intelligence AAAI Workshop
, pp. 91-96
-
-
Hunicke, R.1
Chapman, V.2
-
5
-
-
33749542723
-
Difficulty scaling of game AI
-
Belgium
-
Spronck, P., Sprinkhuizen-Kuyper, I., and Postma, E., "Difficulty Scaling of Game AI". In Proceedings of the 5th International Conference on Intelligent Games and Simulation, Belgium, 2004, pp. 33-37.
-
(2004)
Proceedings of the 5th International Conference on Intelligent Games and Simulation
, pp. 33-37
-
-
Spronck, P.1
Sprinkhuizen-Kuyper, I.2
Postma, E.3
-
6
-
-
29344467694
-
Online coevolution for action games
-
London
-
Demasi, P., and Cruz, A., "Online Coevolution for Action Games". In Proceedings of The 3rd International Conference on Intelligent Games And Simulation, London, 2002, pp. 113-120.
-
(2002)
Proceedings of the 3rd International Conference on Intelligent Games and Simulation
, pp. 113-120
-
-
Demasi, P.1
Cruz, A.2
-
7
-
-
84888133669
-
Analyzing cooperative coevolution with evolutionary game theory
-
IEEE Press, Honolulu
-
Wiegand, R., Liles, W., and Jong, G., "Analyzing Cooperative Coevolution with Evolutionary Game Theory", In Proceedings of the 2002 Congress on Evolutionary Computation, IEEE Press, Honolulu, 2002, pp. 1600-1605.
-
(2002)
Proceedings of the 2002 Congress on Evolutionary Computation
, pp. 1600-1605
-
-
Wiegand, R.1
Liles, W.2
Jong, G.3
-
8
-
-
0029679044
-
Reinforcement learning: A survey
-
AAAI Press
-
Kaelbling, L., Littman, M., and Moore, A.," Reinforcement Learning: A Survey", Journal of Artificial Intelligence Research, AAAI Press, 1996, pp.4:237-285.
-
(1996)
Journal of Artificial Intelligence Research
, vol.4
, pp. 237-285
-
-
Kaelbling, L.1
Littman, M.2
Moore, A.3
-
9
-
-
32144442027
-
Bootstrapping the learning process for the semi-automated design of a challenging game AI
-
San Jose
-
Madeira, C., Corruble, V., Ramalho, G., and Ratitch, B.," Bootstrapping the Learning Process for the Semi-automated Design of a Challenging Game AI". Challenges in Game Artificial Intelligence AAAI Workshop, San Jose, 2004, pp. 72-76.
-
(2004)
Challenges in Game Artificial Intelligence AAAI Workshop
, pp. 72-76
-
-
Madeira, C.1
Corruble, V.2
Ramalho, G.3
Ratitch, B.4
-
10
-
-
33846268789
-
Challenge-sensitive action selection: An application to game balancing
-
September 19-22, [doi>10.1109/IAT.2005.52
-
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vincent Corruble, Challenge-Sensitive Action Selection: an Application to Game Balancing, Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology, p.194-200, September 19-22, 2005 [doi>10.1109/IAT.2005.52].
-
(2005)
Proceedings of the IEEE/WIC/ACM International Conference on Intelligent Agent Technology
, pp. 194-200
-
-
Andrade, G.1
Ramalho, G.2
Santana, H.3
Corruble, V.4
-
12
-
-
33947679371
-
Flow in games (and everything else)
-
April
-
Chen, J. Flow in games (and everything else), Communications of the ACM, v.50 n.4, April 2007.
-
(2007)
Communications of the ACM
, vol.50
, Issue.4
-
-
Chen, J.1
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