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

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Andrew ChiouAuthors Info & Claims

DIMEA '07: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts

Pages 91 - 97

https://doi.org/10.1145/1306813.1306837

Published: 19 September 2007 Publication History

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Abstract

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.

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Rumsamrong MChiou A(2018)CRISIS-ExpertProceedings of the 2018 International Conference on Computational Intelligence and Intelligent Systems10.1145/3293475.3293478(14-19)Online publication date: 17-Nov-2018
https://dl.acm.org/doi/10.1145/3293475.3293478
Chiou AWong K(2010)Auto-explanation System: Player Satisfaction in Strategy-Based Board GamesCultural Computing10.1007/978-3-642-15214-6_5(46-54)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15214-6_5
Chiou AWong K(2008)Player Adaptive Entertainment Computing (PAEC): Mechanism to model user satisfaction by using Neuro Linguistic Programming (NLP) techniques2008 IEEE Symposium On Computational Intelligence and Games10.1109/CIG.2008.5035660(343-349)Online publication date: Dec-2008
https://doi.org/10.1109/CIG.2008.5035660

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DIMEA '07: Proceedings of the 2nd international conference on Digital interactive media in entertainment and arts

September 2007

212 pages

ISBN:9781595937087

DOI:10.1145/1306813

Conference Chairs:
Kevin Kok Wai Wong
Murdoch University, Australia
,
Lance Fung
Murdoch University, Australia
,
Peter Cole
Murdoch University, Australia

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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SIGCHI: ACM Special Interest Group on Computer-Human Interaction

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Association for Computing Machinery

New York, NY, United States

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Published: 19 September 2007

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DIMEA07: Second International Conference on Digital Interactive Media in Entertainment and Arts

September 19 - 21, 2007

Perth, Australia

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Rumsamrong MChiou A(2018)CRISIS-ExpertProceedings of the 2018 International Conference on Computational Intelligence and Intelligent Systems10.1145/3293475.3293478(14-19)Online publication date: 17-Nov-2018
https://dl.acm.org/doi/10.1145/3293475.3293478
Chiou AWong K(2010)Auto-explanation System: Player Satisfaction in Strategy-Based Board GamesCultural Computing10.1007/978-3-642-15214-6_5(46-54)Online publication date: 2010
https://doi.org/10.1007/978-3-642-15214-6_5
Chiou AWong K(2008)Player Adaptive Entertainment Computing (PAEC): Mechanism to model user satisfaction by using Neuro Linguistic Programming (NLP) techniques2008 IEEE Symposium On Computational Intelligence and Games10.1109/CIG.2008.5035660(343-349)Online publication date: Dec-2008
https://doi.org/10.1109/CIG.2008.5035660

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A game AI production shell framework: generating AI opponents for geomorphic-isometric strategy games via modeling of expert player intuition

Evolutionary algorithm for game difficulty control

An analysis of play style of advanced mahjong players toward the implementation of strong AI player

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