Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2011
Abstract
We apply decision theoretic techniques to construct nonplayer characters that are able to assist a human player in collaborative games. The method is based on solving Markov decision processes, which can be difficult when the game state is described by many variables. To scale to more complex games, the method allows decomposition of a game task into subtasks, each of which can be modelled by a Markov decision process. Intention recognition is used to infer the subtask that the human is currently performing, allowing the helper to assist the human in performing the correct task. Experiments show that the method can be effective, giving nearhuman level performance in helping a human in a collaborative game. Copyright © 2011, Association for the Advancement of Artificial.
Discipline
Artificial Intelligence and Robotics
Publication
7th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2011
First Page
61
Last Page
66
ISBN
9781577355397
City or Country
Palo Alto, CA, USA
Citation
Nguyen T., Hsu D., Lee W., Tze-Yun LEONG, Kaelbling L., Lozano-Perez T., and Grant A..
CAPIR: Collaborative action planning with intention recognition. (2011). 7th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment, AIIDE 2011. 61-66.
Available at: https://ink.library.smu.edu.sg/sis_research/3002
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.