Abstract
This paper proposes syntactic combination rules for merging uncertain propositional knowledge bases provided by different sources of information, in the framework of possibilistic logic. These rules are the counterparts of combination rules which can be applied to the possibility distributions (defined on the set of possible worlds), which represent the semantics of each propositional knowledge base. Combination modes taking into account the levels of conflict, the relative reliability of the sources, or having reinforcement effects are considered.
This is an abbreviated version, where proofs are also omitted, of a paper entitled “From semantic to syntactic approaches to information combination in possibilistic logic” to appear in: Aggregation of Evidence in Fuzziness (B. Bouchon-Meunier ed.), Physica Verlag.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Abidi M.A., Gonzalez R.C. (eds) (1992) Data Fusion in Robotics and Machine Intelligence. Academic Press, New York.
Baral C., Kraus S., Minker J., Subrahmanian (1992) Combining knowledge bases consisting in first order theories. Computational Intelligence, 8(1), 45–71.
Benferhat S., Cayrol C., Dubois D., Lang J., Prade H. (1993) Inconsistency management and prioritized syntax-based entailment. Proc. of the 13th Inter. Joint Conf. on Artificial Intelligence (IJCAI'93), Chambéry, France, Aug. 28–Sept. 3, 640–645.
Boldrin L., Sossai C. (1995) An algebraic semantics for possibilistic logic. Proc of the 11th Conf. Uncertainty in Artifucial Intelligence (P. Besnard, S. Hank, eds.),27–35.
Cholvy F. (1992) A logical approach to multi-sources reasoning. In: Applied Logic Conference: Logic at Work, Amsterdam.
Dubois D., Lang J., Prade H. (1987) Theorem proving under uncertainty— A possibility theory-based approach. Proc. of the 10th Inter. Joint Conf. on Artificial Intelligence, Milano, Italy, August, 984–986.
Dubois D., Lang J., Prade H. (1992) Dealing with multi-source information in possibilistic logic. Proc. of the 10th Europ. Conf. on Artificial Intelligence (ECAI'92) Vienna, 38–42.
Dubois D., Lang J., Prade H. (1994) Possibilistic logic. In: Handbook of Logic in Artificial Intelligence and Logic Programming — Vol 3: Nonmonotonic Reasoning and Uncertain Reasoning (Dov M. Gabbay et al., eds.), Oxford Univ. Press, 439–513.
Dubois D., Prade H. (1988a) Possibility Theory — An Approach to Computerized Processing of Uncertainty. Plenum Press, New York.
Dubois D., Prade H. (1988b) Representation and combination of uncertainty with belief functions and possibility. Computational Intelligence, 4, 244–264.
Dubois D., Prade H. (1988c) Default reasoning and possibility theory. Artificial Intelligence, 35, 243–257.
Dubois D., Prade H. (1988d) On the combination of uncertain or imprecise pieces of information in rule-based systems. A discussion in a framework of possibility theory. Int. Journal of Approximate Reasoning, 2, 65–87.
Dubois D., Prade H. (1990) Aggregation of possibility measures. In: Multiperson Decision Making Using Fuzzy Sets and Possibility Theory (J. Kacprzyk, M. Fedrizzi, eds.), Kluwer Academic Publ., 55–63.
Dubois D., Prade H. (1992) Combination of fuzzy information in the framework of possibility theory. In: Data Fusion in Robotics and Machine Intelligence (M.A. Abidi, R.C. Gonzalez, eds.) Academic Press, New York, 481–505.
Dubois D., Prade H. (1996) Belief revision with uncertain inputs in the possibilistic setting. Proc. of the 12th Conf. on Uncertainty in Artificial Intelligence (E. Horvitz et al., eds.), Portland, 236–243
Flamm J., Luisi T. (Eds.) (1992) Reliability Data and Analysis. Kluwer Academic Publ.
Kelman A. (1996) Modèles flous pour l'agrégation de données et l'aide á la décision. Thèse de Doctorat, Université Paris 6, France.
Matzkevich I, Abramson B. (1992) The topological fusion of Bayes nets. Proc. of the 8th Conf. on Uncertainty in Artificial Intelligence (D. Dubois et al., eds.), pp. 191–198.
Williams M.A. (1996) Towards a practical approach to belief revision: Reason-based change. Proc. of the 5th Conf. on Knowledge Representation and Reasoning Principles (KR'96).
Yager R.R. (1987) On the Dempster-Shafer framework and new combination rules. Information Sciences, 41, 93–138.
Yager R. R. (1991) Non-monotonic set-theoritic operators. Fuzzy Sets and Systems 42, 173–190.
Zadeh L.A. (1978) Fuzzy sets as a basis for a theory of possibility. Fuzzy Sets and Systems, 1, 3–28.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Benferhat, S., Dubois, D., Prade, H. (1997). Syntactic combination of uncertain information: A possibilistic approach. In: Gabbay, D.M., Kruse, R., Nonnengart, A., Ohlbach, H.J. (eds) Qualitative and Quantitative Practical Reasoning. FAPR ECSQARU 1997 1997. Lecture Notes in Computer Science, vol 1244. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0035610
Download citation
DOI: https://doi.org/10.1007/BFb0035610
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63095-1
Online ISBN: 978-3-540-69129-7
eBook Packages: Springer Book Archive