Planning for conjunctive goals
Artificial Intelligence
Planning as search: a quantitative approach
Artificial Intelligence
Towards a computational theory of cognitive maps
Artificial Intelligence
Incremental learning of concept descriptions: A method and experimental results
Machine intelligence 11
Creativity and learning in a case-based explainer
Artificial Intelligence
Computational vision
Active perception and reinforcement learning
Proceedings of the seventh international conference (1990) on Machine learning
Explanation-Based Generalization: A Unifying View
Machine Learning
Exploratory learning structures in artificial cognitive systems
Image and Vision Computing
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The construction of robots adequate for field operation requires the integration of planning, perception, and learning. The coordination of these technologies in the context of constraints of realtime, robust, and safe operation is leading to coupled representations of perception and action. We are developing a system that explores the use of Case-Based Reasoning techniques for inducing low-level, coupled representations of potential robot locations. These will subsequently be used for planning and possibly as operationality criteria in deriving efficient task description. This work is proceeding under an architectural design that integrates horizontal, subsumption approaches to building robots with the vertical Perception-Control-Action internal structure for each layer.