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Creating appropriate challenge level game opponent by the use of dynamic difficulty adjustment.

, , , , , , and . ICNC, page 3897-3901. IEEE, (2010)

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Creating appropriate challenge level game opponent by the use of dynamic difficulty adjustment., , , , , , and . ICNC, page 3897-3901. IEEE, (2010)Game Player Strategy Pattern Recognition by Using Radial Basis Function., , , , , , and . CSSE (1), page 937-940. IEEE Computer Society, (2008)To Create Intelligent Adaptive Neuro-Controller of Game Opponent from UCT-Created Data., , , , , , and . FSKD (2), page 445-449. IEEE Computer Society, (2009)Automatic AI design by the use of MCTS for the game Dead-End., , , , and . FSKD, page 2772-2776. IEEE, (2010)Strategy-Based Player Modeling during Interactive Entertainment Sessions by Using Bayesian Classification., , , , and . ICNC (4), page 255-261. IEEE Computer Society, (2008)Game Player Strategy Pattern Recognition and How UCT Algorithms Apply Pre-knowledge of Player's Strategy to Improve Opponent AI., , , , , , , and . CIMCA/IAWTIC/ISE, page 1177-1181. IEEE Computer Society, (2008)Creating Challengeable and Satisfactory Game Opponent by the Use of CI Approaches., , , , and . Int. J. Adv. Comp. Techn., 2 (1): 41-63 (2010)Dynamic Difficulty Adjustment of Game AI by MCTS for the game Pac-Man., , , , , and . ICNC, page 3918-3922. IEEE, (2010)To Create Intelligent Adaptive Game Opponent by Using Monte-Carlo for the Game of Pac-Man., , , , , , and . ICNC (5), page 598-602. IEEE Computer Society, (2009)Optimizing player's satisfaction through DDA of game AI by UCT for the Game Dead-End., , , , , , and . ICNC, page 4161-4165. IEEE, (2010)