Abstract
This paper makes the first attempt to establish a framework for possibilistic reasoning in (nonmonotonic) multi-context systems, called possibilistic MCS. We first introduce the syntax for possibilistic MCS and then define its equilibrium semantics based on Brewka and Eiter’s nonmonotonic multi-context systems. Then we investigate several properties and develop a fixoint theory for possibilistic MCS.
Access provided by Autonomous University of Puebla. Download to read the full chapter text
Chapter PDF
Similar content being viewed by others
Keywords
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
References
Benferhat, S., Sossai, C.: Reasoning with multiple-source information in a possibilistic logic framework. Information Fusion 7, 80–96 (2006)
Bettini, C., Brdiczka, O., Henricksen, K., Indulska, J., Nicklas, D., Ranganathan, A., Riboni, D.: A survey of context modelling and reasoning techniques. Pervasive and Mobile Computing 6(2), 161–180 (2010)
Bikakis, A., Patkos, T., Antoniou, G., Plexousakis, D.: A Survey of Semantics-Based Approaches for Context Reasoning in Ambient Intelligence. In: Mühlhäuser, M., Ferscha, A., Aitenbichler, E. (eds.) AmI 2007 Workshops. CCIS, vol. 11, pp. 14–23. Springer, Heidelberg (2008)
Brewka, G., Eiter, T.: Equilibria in heterogeneous nonmonotonic multi-context systems. In: Proc. AAAI, pp. 385–390 (2007)
Brewka, G., Roelofsen, F., Serafini, L.: Contextual default reasoning. In: Proc. IJCAI, pp. 268–273 (2007)
Dubois, D., Lang, J., Prade, H.: Possibilistic logic. In: Handbook of Logic in Artificial Intelligence and Logic Programming, vol. 3, pp. 439–513 (1995)
Serafini, L., Giunchiglia, F.: Multilanguage hierarchical logics, or: how we can do without modal logics. In: Artificial Intelligence, pp. 29–70 (1994)
Gelfond, M., Lifschitz, V.: The stable model semantics for logic programming. In: Proc. 5th ICLP, pp. 1070–1080 (1988)
Lloyd, J.W.: Foundations of Logic Programming, 2nd edn. Springer, New York (1987)
McCarthy, J.: Notes on formalizing context. In: Proc. IJCAI, pp. 555–560 (1993)
Nicolas, P., Garcia, L., Stéphan, I., Lefèvre, C.: Possibilistic uncertainty handling for answer set programming. In: Annals of Mathematics and Artificial Intelligence, pp. 139–181 (2006)
Roelofsen, F., Serafini, L.: Minimal and absent information in contexts. In: Proc. IJCAI, pp. 558–563 (2005)
Yager, R.R.: An introduction to applications of possibility theory. Human Syst. Manag., 246–269 (1983)
Zadeh L.A.: Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 3–28 (1978)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jin, Y., Wang, K., Wen, L. (2012). Possibilistic Reasoning in Multi-Context Systems: Preliminary Report. In: Anthony, P., Ishizuka, M., Lukose, D. (eds) PRICAI 2012: Trends in Artificial Intelligence. PRICAI 2012. Lecture Notes in Computer Science(), vol 7458. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32695-0_18
Download citation
DOI: https://doi.org/10.1007/978-3-642-32695-0_18
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32694-3
Online ISBN: 978-3-642-32695-0
eBook Packages: Computer ScienceComputer Science (R0)