Abstract
The problem of merging or combining multiple sources information is central in many information processing areas such as databases integrating problems, expert opinion pooling, preference aggregation, etc. Possibilistic logic offers a qualitative framework for representing pieces of information associated with levels of uncertainty or priority. This paper discusses the fusion of multiple sources information in this setting. Different classes of merging operators are considered, at the semantic and the syntactic level, including conjunctive, disjunctive, reinforcement, adaptive and averaging operators. This framework appears to be the syntactic counterpart of the pointwise aggregation of possibility distributions or fuzzy sets.
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References
M.A. Abidi, R.C. Gonzalez (Eds.). Data Fusion in Robotics and Machine Intelligence. Academic Press, New York.
C. Baral, S. Kraus, J. Minker, Subrahmanian. Combining knowledge bases consisting in first order theories, Computational Intelligence, 8 (1), 45–71, 1992.
S. Benferhat, D. Dubois, S. Kaci, H. Prade. Encoding information fusion in possibilistic logic: A general framework for rational syntactic merging. In Proceedings of 14`h ECAI, 3–7, 2000.
S. Benferhat, D. Dubois, H. Prade. How to infer from inconsistent beliefs without revising ? In Proceedings of 14°h IJCAI, 20–25, 1449–1455, 1995.
S. Benferhat, D. Dubois, H. Prade. From semantic to syntactic approaches to information combination in possibilistic logic, Aggregation and Fusion of Imperfect Information (B. Bouchon-Meunier, Ed.), Physica-Verlag, Heidelberg, Germany, 141–161, 1997.
S. Benferhat, D. Dubois, H. Prade, M. Williams, A practical approach to fusing and revising prioritized belief bases. In Proceedings of EPIA 99. LNAI n° 1695, Springer Verlag, 222–236.
B. Bouchon-Meunier, Ed. Aggregation and Fusion of Imperfect Information, Physica-Verlag, 1997.
L. Cholvy. A logical approach to multi-sources reasoning. In Applied Logic Conference: Logic at Work, Amsterdam
D. Dubois, J. Lang, H. Prade, Possibilistic logic. In Handbook of Logic in Artificial Intelligence and Logic Programming, Vol. 3, 439–513, 1994.
D. Dubois, H. Prade. Possibility theory and data fusion in poorly informed environments, Control Engineering Practice, 2 (5), 811–823, 1994.
D. Dubois, H. Prade, R. Yager. Merging fuzzy information, Fuzzy Sets in Approximative Reasoning and Information Systems, (J.C. Bezdek, D. Dubois, H. Prade Eds.). The Handbboks of Fuzzy Sets Series, Kluwer Academic Publisher, Dordrecht, 335–401, 1999.
J. Flamm, T. Luisi (Eds.) Reliability Data and Analysis. Kluwer Academic Publishers.
M. Grabisch, S. Orlovski, R. Yager. Fuzzy aggregations of numerical preferences, Fuzzy Sets in Decision Analysis, Operations Research and Statistics, (R. Slowinski, Ed). The Handbooks of Fuzzy Sets Series, Kluwer Academic Publishers, Dordrecht, 31–68, 1998.
J. Kacprzyk, H. Nurmi. Group decision making under fuzziness, Fuzzy Sets in Decision Analysis, Operations Research and Statistics, (R. Slowinski Ed.). The Handbooks of Fuzzy Sets Series, Kluwer Academic Publisher, Dordrecht, The Netherlands, 103–136, 1998.
S. Konieczny, R.Pino Pérez, On the logic of merging. In Proceedings of the 6th International Conference on Principles of Knowledge Representation and Reasoning (KR’98), 488–498, 1998.
S. Konieczny, R. Pino Pérez, Merging with integrity constraints. In Proceedings of ECSQARU’99, LNAI n° 1638, Springer Verlag, 233–244, 1999.
J. Lin, Integration of weighted knowledge bases, Artificial Intelligence 83, 363378, 1996.
J. Lin, A.O. Mendelzon, Merging databases under constraints,1998. International Journal of Cooperative Information Systems, 7 (1): 55–76, 1998.
P. Z. Revesz. On the semantics of theory change: arbitration between old and new information. Proceedings of the 12th ACM SIGACT-SIGMOD-SIGART symposium on Principles of Databases, 71–92, 1993.
P. Z. Revesz. On the semantics of arbitration. International Journal of Algebra and Computation, 7 (2), 133–160, 1997.
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Kaci, S., Benferhat, S., Dubois, D., Prade, H. (2003). Possibilistic Logic: A Theoretical Framework for Multiple Source Information Fusion. In: Reznik, L., Kreinovich, V. (eds) Soft Computing in Measurement and Information Acquisition. Studies in Fuzziness and Soft Computing, vol 127. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-36216-6_6
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DOI: https://doi.org/10.1007/978-3-540-36216-6_6
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