Publication Type

Conference Proceeding Article

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

Research Areas

Intelligent Systems and Decision Analytics

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

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