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A Behavior-Authoring Framework for Multiactor Simulations
Nov.-Dec. 2011 (vol. 31 no. 6)
pp. 45-55
Interest has been growing in the behavioral animation of autonomous actors in virtual worlds. However, authoring complicated interactions between multiple actors in a way that balances control flexibility and automation remains a considerable challenge. A proposed behavior-authoring framework gives users complete control over the domain of the system: the state space, action space, and cost of executing actions. To specialize actors, the framework uses effect and cost modifiers, which modify existing action definitions, and constraints, which prune action choices in a state-dependent manner. The framework groups actors with common or conflicting goals to form a composite domain, and a multiagent planner generates complicated interactions between multiple actors. The Web extra is a video that shows how multiactor simulations should aim to strike a happy medium between the automation of generation and the flexibility of specification.

1. R.E. Fikes and N.J. Nilsson, "Strips: A New Approach to the Application of Theorem Proving to Problem Solving," Artificial Intelligence, vol. 2, nos. 3–4, 1971, pp. 189–208.
2. B. Bonet and H. Geffner, "Heuristic Search Planner 2.0," AI Magazine, vol. 22, no. 3, 2001, pp. 77–80.
1. N. Pelechano, J. Allbeck, and N. Badler, Virtual Crowds: Methods, Simulation, and Control, Morgan & Claypool, 2008.
2. A.B. Loyall, "Believable Agents: Building Interactive Personalities," doctoral thesis, Computer Science Dept., Carnegie Mellon Univ., 1997.
3. M. Mateas, "Interactive Drama, Art and Artificial Intelligence," doctoral thesis, Computer Science Dept., Carnegie Mellon Univ., 2002.
4. A. Braun et al., "Modeling Individual Behaviors in Crowd Simulation," Proc. 16th Int'l Conf. Computer Animation and Social Agents (CASA 03), IEEE CS Press, 2003, p. 143.
5. F. Durupinar et al., "Creating Crowd Variation with the Ocean Personality Model," Proc. 7th Int'l Joint Conf. Autonomous Agents and Multiagent Systems (AAMAS 08), Int'l Foundation for Autonomous Agents and Multiagent Systems, 2008, pp. 1217–1220.
6. C. Stocker et al., "Smart Events and Primed Agents," Proc. 10th Int'l Conf. Intelligent Virtual Agents (IVA 10), Springer, 2010, pp. 15–27.
7. K. Perlin and A. Goldberg, "Improv: A System for Scripting Interactive Actors in Virtual Worlds," Proc. Siggraph, ACM Press, 1996, pp. 205–216.
8. E. Menou, "Real-Time Character Animation Using Multi-layered Scripts and Spacetime Optimization," Proc. Int'l Conf. Virtual Storytelling (ICVS 01), Springer, 2001, pp. 135–144.
9. Q. Yu and D. Terzopoulos, "A Decision Network Framework for the Behavioral Animation of Virtual Humans," Proc. ACM Siggraph/Eurographics Symp. Computer Animation (SCA 07), Eurographics Assoc., 2007, pp. 119–128.
10. R.E. Fikes and N.J. Nilsson, "Strips: A New Approach to the Application of Theorem Proving to Problem Solving," Artificial Intelligence, vol. 2, nos. 3–4, 1971, pp. 189–208.
11. J. Funge, X. Tu, and D. Terzopoulos, "Cognitive Modeling: Knowledge, Reasoning and Planning for Intelligent Characters," Proc. Siggraph, ACM Press, 1999, pp. 29–38.

Index Terms:
Virtual environments,Trajectory,Computational modeling,Video communication,graphics and multimedia,crowds,high-level behaviors,coordination,authoring,virtual worlds,computer graphics
Citation:
M. Kapadia, S. Singh, G. Reinman, P. Faloutsos, "A Behavior-Authoring Framework for Multiactor Simulations," IEEE Computer Graphics and Applications, vol. 31, no. 6, pp. 45-55, Nov.-Dec. 2011, doi:10.1109/MCG.2011.68
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