KR2020Proceedings of the 17th International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 17th International Conference on Principles of Knowledge Representation and Reasoning

Rhodes, Greece. September 12-18, 2020.

Edited by

ISSN: 2334-1033
ISBN: 978-0-9992411-7-2

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Copyright © 2020 International Joint Conferences on Artificial Intelligence Organization

A Preference-Based Approach to Defeasible Deontic Inference

  1. James Delgrande(Simon Fraser University)


  1. Reasoning about knowledge, beliefs, and other mental attitudes-General
  2. Nonmonotonic logics, default logics, conditional logics-General
  3. Modeling and reasoning about preferences-


In this paper we present an approach to defeasible deontic inference.

Given a set of rules R expressing conditional obligations and a formula A giving contingent information, the goal is to determine the most desirable outcome with respect to this information.

Semantically, the rules R induce a partial preorder on the set of models, giving the relative desirability of each model.

Then the set of minimal A models characterises the best that can be attained given that A holds.

A syntactic approach is also given, in terms of maximal subsets of material counterparts of rules in R, and that yields a formula that expresses the best outcome possible given that A holds.

These approaches are shown to coincide, providing an analogue to a soundness and completeness result.

Complexity is not unreasonable, being at the second level of the polynomial hierarchy when the underlying logic is propositional logic.

The approach yields desirable and intuitive results, including for the various “paradoxes” of deontic reasoning.

The approach also highlights an interesting difference in how specificity is dealt with in nonmonotonic and deontic reasoning.