Robert C. Burke

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Compelling synthetic characters must behave in ways that reflect their past experience and thus allow for individual personalization. We therefore need a method that allows characters to learn. But simply adding traditional machine learning algorithms without considering the characters' own motivations and desires will break the illusion of life.(More)
This paper describes a new layered brain architecture for simulated autonomous and semi-autonomous creatures that inhabit graphical worlds. The main feature of the brain is its division into distinct systems, which communicate through common access to an internal mental blackboard. The brain was designed to encourage experimentation with various systems and(More)
Inspired by recent work in ethology and animal training, we integrate representations for time and rate into a behavior-based architecture for autonomous virtual creatures. The resulting computational model of affect and action selection allows creatures to discover and refine their understanding of apparent temporal causality relationships which may or may(More)
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