A Framework for the Analysis of Sophisticated Control in Interpretation Systems
Robert C. Whitehair, Victor Lesser · 1993
This paper introduces a framework for the analysis of sophisticated search control architectures in AI systems. The framework is based on two formalisms, the Interpretation Decision Problem (IDP), which models the characteristics and problem structure of a domain, and the UPC formalism, which provides a general model of control and problem solving. Using these models, the problem structures of disparate domains and the problem solving architectures constructed to exploit these structures can be viewed from a unified perspective where control and problem solving actions can be considered a single class of problem solving activity. Models built from this unified perspective offer advantages for describing, predicting and explaining the behavior of interpretation systems and for generalizing a specific problem solving architecture to other domains. Use of the IDP and UPC formalisms also supports the synthesis of new, more flexible problem solving architectures. Examples based on formalizing uncertainty and subproblem interaction are used to illustrate the power of the IDP/UPC framework.