A Study on Adaptive Game AI
Computer-controlled opponents in most games change their tactics in a finite manner. After playing several times, the human player will recognize the repetition of tactics adopted by the computer-
controlled opponents, and then the player will get bored at the game. Hence, in recent years game developers have paid more resources on developing challenging games. For most games, high- quality game AI is the key to providing challenging gameplay. Game AI is defined as the decision-making process of computer-controlled opponents in computer games. It is called adaptive if the computer- controlled opponents can automatically fix weaknesses in the game AI and respond to changes in player’s tactics during gameplay.
Adaptive game AI is currently in its infancy. This three-year project aims to develop adaptive game AI for both online and offline
adaptation of tactics. First, in this project we will develop various tactics to fit human players with different gameplay experience by using offline adaptive game AI and player modeling. Next, we will develop new online adaptive game AI to improve the tactics of the computer-controlled opponents based on the player’s behaviors, and enhance challenge and entertainment value by using dynamic- difficulty-adjustment techniques. Third, our accumulated experience at adaptive game AI will be applied to educational games to
enhance their entertaining and learning effects. Finally, an
evaluation of the developed adaptive game AI on educational games will be performed. The research results of this project will forward the developments of adaptive game AI in both entertaining and educational games.
Keywords: Adaptive game AI, online adaptive game AI, offline adaptive game AI, player modeling, educational games,
performance evaluation
