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Title:Simulating Interactions of Avatars in High Dimensional State Space
Authors: Pak Ho Shum ; Taku Komura ; Masashi Shiraishi ; Shuntaro Yamazaki
Date:Mar 2008
Publication Title:ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games 2008
Publication Type:Conference Paper Publication Status:Published
Page Nos:131-138
DOI:: ISBN/ISSN:978-1-59593-983-8
Efficient computation of strategic movements is essential to control virtual avatars intelligently in computer games and 3D virtual environments. Such a module is needed to control non-player characters (NPCs) to fight, play team sports or move through a mass crowd. Reinforcement learning is an approach to achieve real-time optimal control. However, the huge state space of human interactions makes it difficult to apply existing learning methods to control avatars when they have dense interactions with other characters. In this research, we propose a new methodology to efficiently plan the movements of an avatar interacting with another. We make use of the fact that the subspace of meaningful interactions is much smaller than the whole state space of two avatars. We efficiently collect samples by exploring the subspace where dense interactions between the avatars occur and favor samples that have high connectivity with the other samples. Using the collected samples, a finite state machine (FSM) called Interaction Graph is composed. At run-time, we compute the optimal action of each avatar by minmax search or dynamic programming on the Interaction Graph. The methodology is applicable to control NPCs in fighting and ball-sports games.
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Bibtex format
author = { Pak Ho Shum and Taku Komura and Masashi Shiraishi and Shuntaro Yamazaki },
title = {Simulating Interactions of Avatars in High Dimensional State Space},
book title = {ACM SIGGRAPH Symposium on Interactive 3D Graphics and Games 2008},
publisher = {ACM},
year = 2008,
month = {Mar},
pages = {131-138},
doi = {:},
url = {},

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