Transforming Prioritized Defaults and Specificity into Parallel Defaults
Benjamin N. Grosof

TL;DR
This paper introduces a method to convert prioritized propositional defaults into equivalent unprioritized defaults within circumscription, enabling more flexible and comprehensive default reasoning algorithms.
Contribution
The authors present an algorithm to transform prioritized defaults into parallel defaults, allowing for non-layered prioritization and improved default inheritance modeling.
Findings
Provides a new query-answering algorithm for unrestricted finite prioritization
Enables implementation of non-layered prioritization in circumscription
Discusses practical inference methods despite exponential worst-case complexity
Abstract
We show how to transform any set of prioritized propositional defaults into an equivalent set of parallel (i.e., unprioritized) defaults, in circumscription. We give an algorithm to implement the transform. We show how to use the transform algorithm as a generator of a whole family of inferencing algorithms for circumscription. The method is to employ the transform algorithm as a front end to any inferencing algorithm, e.g., one of the previously available, that handles the parallel (empty) case of prioritization. Our algorithms provide not just coverage of a new expressive class, but also alternatives to previous algorithms for implementing the previously covered class (?layered?) of prioritization. In particular, we give a new query-answering algorithm for prioritized cirumscription which is sound and complete for the full expressive class of unrestricted finite prioritization partial…
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Taxonomy
TopicsLogic, Reasoning, and Knowledge · Bayesian Modeling and Causal Inference · AI-based Problem Solving and Planning
