Belief Change in a Preferential Non-Monotonic Framework
Casini, Giovanni and Thomas Meyer (2017) Belief Change in a Preferential Non-Monotonic Framework. In Sierra, Carles, Eds. Proceedings International Joint Conference on Artificial Intelligence (IJCAI), pages 925-935, Melbourne, Australia.
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.
|EPrint Type:||Conference Paper|
|Subjects:||I Computing Methodologies: I.2 ARTIFICIAL INTELLIGENCE|
|Deposited By:||Meyer, Thomas|
|Deposited On:||23 November 2017|