Abstract
For intelligent systems to interact with external agents and changing domains, they must be able to perceive and to affect their environments while computing long term projection (planning) of future states. This paper describes and demonstrates the supervenience architecture, a multilevel architecture for integrating planning and reacting in complex, dynamic environments. We briefly review the underlying concept of supervenience, a form of abstraction with affinities both to abstraction in AI planning systems, and to knowledge-partitioning schemes in hierarchical control systems. We show how this concept can be distilled into a strong constraint on the design of dynamic-world planning systems. We then describe the supervenience architecture and an implementation of the architecture called APE (for Abstraction-Partitioned Evaluator). The application of APE to the HomeBot domain is used to demonstrate the capabilities of the architecture.
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