SOAR: an architecture for general intelligence
Artificial Intelligence
Unified theories of cognition
A preliminary analysis of the Soar architecture as a basis for general intelligence
Artificial Intelligence
Modeling concept acquisition in the context of a unified theory of cognition
Modeling concept acquisition in the context of a unified theory of cognition
Understanding Natural Language
Understanding Natural Language
Soar Papers: Research on Integrated Intelligence
Soar Papers: Research on Integrated Intelligence
Explanation-Based Generalization: A Unifying View
Machine Learning
Toward Incremental Knowledge Correction for Agents in Complex Environments
Machine Intelligence 15, Intelligent Agents [St. Catherine's College, Oxford, July 1995]
Learning procedural planning knowledge in complex environments
Learning procedural planning knowledge in complex environments
Journal of Artificial Intelligence Research
Conceptual Models and Architectures for Advanced Information Systems
Applied Intelligence
An agency-based framework for electronic business
CIA'99 Proceedings of the 3rd international conference on Cooperative information agents III
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Most work on adaptive agents have a simple, single layerarchitecture. However, most agent architectures support three levels ofknowledge and control: a reflex level for reactive responses, a deliberatelevel for goal-driven behavior, and a reflective layer for deliberateplanning and problem decomposition. In this paper we explore agentsimplemented in Soar that behave and learn at the deliberate and reflectivelevels. These levels enhance not only behavior, but also adaptation. Theagents use a combination of analytic and empirical learning, drawing from avariety of sources of knowledge to adapt to their environment. We hypothesize that complete, adaptive agents must be able to learn across all three levels.