Belief Change in a Preferential Non-Monotonic Framework

Casini, Giovanni and Meyer, Thomas (2017) Belief Change in a Preferential Non-Monotonic Framework, Proceedings of International Joint Conference on Artificial Intelligence (IJCAI), 19-25 August, Melbourne, Australia, 925-935, AAAI Press.

[img] PDF

Download (377kB)


Belief change and non-monotonic reasoning are usually viewed as two sides of the same coin, with results showing that one can formally be de- fined in terms of the other. In this paper we show that we can also integrate the two formalisms by studying belief change within a (preferential) non-monotonic framework. This integration relies heavily on the identification of the monotonic core of a non-monotonic framework. We consider belief change operators in a non-monotonic propositional setting with a view towards preserving consistency. These results can also be applied to the preser- vation of coherence—an important notion within the field of logic-based ontologies. We show that the standard AGM approach to belief change can be adapted to a preferential non-monotonic frame- work, with the definition of expansion, contraction, and revision operators, and corresponding repre- sentation results. Surprisingly, preferential AGM belief change, as defined here, can be obtained in terms of classical AGM belief change.

Item Type: Conference paper
Subjects: Computing methodologies > Artificial intelligence
Alternate Locations:
Date Deposited: 23 Nov 2017
Last Modified: 10 Oct 2019 15:31

Actions (login required)

View Item View Item