What is it thinking? : game AI opponent computer-human interaction using descriptive schema and explanatory capabilities

In strategy-based games, it is sometimes beneficial to understand the evaluation processes of the game AI opponent, e.g. What strategic or tactical motives is it inferring? Why did it make the previous move? However, the mechanics available to allow the game AI to convey these processes to the [human] player or game designer is complex to implement, more so than the actual mechanics of the game AI itself. This paper proposes a method that provides the mechanism for a game AI to communicate its evaluation processes using descriptive schemata and explanatory functions. A case study will be presented that includes an implementation of a game AI opponent that is capable of describing its inferential processes while playing a tabletop wargame

What is it thinking? : game AI opponent computer-human interaction using descriptive schema and explanatory capabilities

In strategy-based games, it is sometimes beneficial to understand the evaluation processes of the game AI opponent, e.g. What strategic or tactical motives is it inferring? Why did it make the previous move? However, the mechanics available to allow the game AI to convey these processes to the [human] player or game designer is complex to implement, more so than the actual mechanics of the game AI itself. This paper proposes a method that provides the mechanism for a game AI to communicate its evaluation processes using descriptive schemata and explanatory functions. A case study will be presented that includes an implementation of a game AI opponent that is capable of describing its inferential processes while playing a tabletop wargame

Chess software and its impact on chess players

Computer-aided chess is an important teaching method, as it allows a student to play under every condition possible, and regulates the speed of his/her development at an incremental pace, measured against actual players in the rated chess community. It is also relatively inexpensive, and pervasive, and allows players to match themselves against competitors from across the world. The learning process extends beyond games, as interactive software has shown it teaches several skills, such as opening, strategy, tactics, and chess-problem solving. Furthermore, current applications allow chess players to establish rankings via online chess tournaments, meet international grandmasters, and have access to training tools based on strategies from chess masters. Using 250 chess software packages, this research classifies them into distinct categories based mainly on the Gobet and Jansen's organization of the chess knowledge. This is followed by extensive discussion that analyzes these training tools, in order to identify the best training techniques available building on a research on human computer interaction, cognitive psychology, and chess theory. --P.ii.The original print copy of this thesis may be available here: http://wizard.unbc.ca/record=b151379