Artificial Intelligence
Artificial Intelligence
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Intelligence without representation
Artificial Intelligence
Made-up minds: a constructivist approach to artificial intelligence
Made-up minds: a constructivist approach to artificial intelligence
Artificial fishes: physics, locomotion, perception, behavior
SIGGRAPH '94 Proceedings of the 21st annual conference on Computer graphics and interactive techniques
Motivation driven learning for interactive synthetic characters
AGENTS '00 Proceedings of the fourth international conference on Autonomous agents
Testing for Periodicity in Signals:an Application to Detect Partial Upper Airway Obstruction during Sleep
Old tricks, new dogs: ethology and interactive creatures
Old tricks, new dogs: ethology and interactive creatures
A layered brain architecture for synthetic creatures
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
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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 not involve self-action. The fundamental action selection choice that a creature must make in order to satisfy its internal needs is whether to explore, react or exploit. In this architecture, that choice is informed by an understanding of apparent temporal causality, the representation for which is integrated into the representation for action. The ability to accommodate changing ideas about causality allows the creature to exist in and adapt to a dynamic world. Not only is such a model suitable for computational systems, but its derivation from biological models suggests that it may also be useful for gaining a new perspective on learning in biological systems. The implementation of a complete character built using this architecture is able to reproduce a variety of conditioning phenomena, as well as learn in real-time using a training technique used with live animals.