Using a constructive interactive activation and competition neural network to construct a situated agent's experience

Authors:
Wei Peng;John S. Gero
Affiliations:
Key Centre of Design Computing and Cognition, University of Sydney, NSW, Australia;Key Centre of Design Computing and Cognition, University of Sydney, NSW, Australia
Venue:
PRICAI'06 Proceedings of the 9th Pacific Rim international conference on Artificial intelligence
Year:
2006

Citing 2
Cited 1

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Knowledge-Based Systems

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Abstract

This paper presents an approach that uses a Constructive Interactive Activation and Competition (CIAC) neural network to model a situated agent's experience. It demonstrates an implemented situated agent and its learning mechanisms. Experiments add to the understanding of how the agent learns from its interactions with the environment. The agent can develop knowledge structures and their intentional descriptions (conceptual knowledge) specific to what it is confronted with - its experience. This research is presented within the design optimization domain.