Talks and Poster Presentations (with Proceedings-Entry):

G. Brewka, J. Mailly, S. Woltran:
"Translation-Based Revision and Merging for Minimal Horn Reasoning";
Talk: ECAI 2016 - 22nd European Conference on Artificial Intelligence, Den Haag, Niederlande; 2016-08-29 - 2016-09-02; in: "Proceedings of the 22nd European Conference on Artificial Intelligence", G. Kaminka, M. Fox, P. Bouquet, E. Hüllermeier, V. Dignum, F. Dignum, F. van Harmelen (ed.); IOS Press, Frontiers in Artificial Intelligence and Applications 285 (2016), ISBN: 978-1-61499-671-2; 734 - 742.

English abstract:
In this paper we introduce a new approach for revising and merging consistent Horn formulae under minimal model semantics. Our approach is translation-based in the following sense: we generate a propositional encoding capturing both the syntax of the original Horn formulae (the clauses which appear or not in them) and their semantics (their minimal models). We can then use any classical revision or merging operator to perform belief change on the encoding. The resulting propositional theory is then translated back into a Horn formula. We identify some specific operators which guarantee a particular kind of minimal change. A unique feature of our approach is that it allows us to control whether minimality of change primarily relates to the syntax or to the minimal model semantics of the Horn formula. We give an axiomatic characterization of minimal change on the minimal model for this new setting, and we show that some specific translation-based revision and merging operators satisfy our postulates.

Created from the Publication Database of the Vienna University of Technology.