From Semantic to Syntactic Approaches to Information Combination in Possibilistic Logic

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.

[1]  Y. Shoham.  Reasoning About Change: Time and Causation from the Standpoint of Artificial Intelligence , 1987 .

[2]  Luca Boldrin,et al.  A Substructural Connective for Possibilistic Logic , 1995, ECSQARU.

[3]  J. Flamm,et al.  Reliability data collection and analysis , 1992 .

[4]  Dov M. Gabbay,et al.  Handbook of logic in artificial intelligence and logic programming (vol. 1) , 1993 .

[5]  Mary-Anne Williams,et al.  Towards a Practical Approach to Belief Revision: Reason-Based Change , 1996, KR.

[6]  Didier Dubois,et al.  Default Reasoning and Possibility Theory , 1988, Artif. Intell..

[7]  Didier Dubois,et al.  Belief Revision with Uncertain Inputs in the Possibilistic Setting , 1996, UAI.

[8]  D. Dubois,et al.  Possibility theory and data fusion in poorly informed environments , 1994 .

[9]  Laurence Cholvy,et al.  A Logical Approach to Multi-Sources Reasoning , 1992, Logic at Work.

[10]  Bruce Abramson,et al.  Some Complexity Considerations in the Combination of Belief Networks , 1993, UAI.

[11]  Didier Dubois,et al.  Theorem Proving Under Uncertainty - A Possibility Theory-based Approach , 1987, IJCAI.

[12]  Didier Dubois,et al.  How to Infer from Inconsisent Beliefs without Revising? , 1995, IJCAI.

[13]  Didier Dubois,et al.  Aggregation of Possibility Measures , 1990 .

[14]  Didier Dubois,et al.  Automated Reasoning Using Possibilistic Logic: Semantics, Belief Revision, and Variable Certainty Weights , 1994, IEEE Trans. Knowl. Data Eng..

[15]  Didier Dubois,et al.  Possibility Theory - An Approach to Computerized Processing of Uncertainty , 1988 .

[16]  Luca Boldrin,et al.  An Algebraic Semantics for Possibilistic Logic , 1995, UAI.

[17]  Didier Dubois,et al.  Inconsistency Management and Prioritized Syntax-Based Entailment , 1993, IJCAI.

[18]  R. Yager.  Non-monotonic set theoretic operations , 1991 .

[19]  Didier Dubois,et al.  Dealing with Multi-Source Information in Possibilistic Logic , 1992, ECAI.

[20]  Henri Prade,et al.  Representation and combination of uncertainty with belief functions and possibility measures , 1988, Comput. Intell..

[21]  Didier Dubois,et al.  On the combination of uncertain or imprecise pieces of information in rule-based systems-A discussion in the framework of possibility theory , 1988, Int. J. Approx. Reason..

[22]  Antoine Kelman.  Modeles flous pour l'agregation de donnees et l'aide a la decision , 1996 .

[23]  L. Zadeh.  Fuzzy sets as a basis for a theory of possibility , 1999 .

[24]  Glenn Shafer,et al.  A Mathematical Theory of Evidence , 2020, A Mathematical Theory of Evidence.

[25]  R. Yager.  On the dempster-shafer framework and new combination rules , 1987, Inf. Sci..

[26]  Bruce Abramson,et al.  The Topological Fusion of Bayes Nets , 1992, UAI.

[27]  H. Prade,et al.  Possibilistic logic , 1994 .

[28]  Mongi A. Abidi,et al.  Data fusion in robotics and machine intelligence , 1992 .