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Control for Autonomy

Providing a virtual human with human-like reactions and decision-making is more complicated than controlling its joint motions from captured or synthesized data. Here is where we engage the viewer with the character's personality and demonstrate its skill and intelligence in negotiating its environment, situation, and other agents. This level of performance requires significant investment in decision-making tools. We presently use a two level architecture:

The architecture is built on Parallel Transition Networks (PaT-Nets) [3]. Nodes represent executable processes, edges contain conditions which when true cause transitions to another node (process), and a combination of message passing and global memory provide coordination and synchronization across multiple parallel processes. Elsewhere we have shown how this architecture can be applied to the game of ``Hide and Seek'' [4], to two person animated conversation [9], or to simulated emergency medical care [10]. Currently we are using this architecture to construct appropriate gestural responses from a synthetic agent, create appropriate visual attention during high-level task execution, manage locomotion tasks, and study multi-agent activity scheduling.

Dr. Norman Badler
Thu Apr 17 08:17:25 EDT 1997