Integrating information theory in agent-based crowd simulation behavior models

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Abstract

Crowds must be simulated believable in terms of their appearance and behavior to improve a virtual environment's realism. Due to the complex nature of human behavior, realistic behavior of agents in crowd simulations is still a challenging problem. In this paper, we propose a novel behavioral model which builds analytical maps to control agents' behavior adaptively with agent-crowd interaction formulations. We introduce information theoretical concepts to construct analytical maps automatically. Our model can be integrated into crowd simulators and enhance their behavioral complexity. We made comparative analyses of the presented behavior model with measured crowd data and two agent-based crowd simulators.

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• Integrating information theory in agent-based crowd simulation behavior models. (deposited 22 Dec 2010 14:40)
  • Integrating information theory in agent-based crowd simulation behavior models. (deposited 28 Dec 2011 11:50) [Currently Displayed]