Strategies for Hypothesis Driven Recognition in Rule Based Systems

Benjamin P. Rode

Recognition continues to be one of the most difficult problems for systems utilizing rule-based reasoning, primarily because of the inadequacy of classical deduction for dealing with the problem and the likelihood of typological mismatch between pattern and data. Following a brief overview of the issues, this paper outlines a hypothesis-driven model for the recognition process that addresses some of the technical challenges while identifying several strategies for implementation based on data characteristics. The conclusion situates the work within a broader biological context.

Subjects: 10. Knowledge Acquisition; 9. Foundational Issue

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