On the relation between possibilistic logic and modal logics of belief and knowledge

Abstract Possibilistic logic and modal logic are knowledge representation frameworks sharing some common features, such as the duality between possibility and necessity, and the decomposability of necessity for conjunctions, as well as some obvious differences since possibility theory is graded. At the semantic level, possibilistic logic relies on possibility distributions and modal logic on accessibility relations. In the last 30 years, there have been a series of attempts for bridging the two frameworks in one way or another. In this paper, we compare the relational semantics of epistemic logics (such as KD45 and S5) with simpler possibilistic semantics of a fragment of such logics that only uses modal formulas of depth 1. This minimal epistemic logic handles both all-or-nothing beliefs and explicitly ignored facts. We also contrast epistemic logic with the S5-based rough set logic. Finally, this paper presents extensions of generalized possibilistic logic with objective and non-nested multimodal formulas, in the style of modal logics KD45 and S5.

[1]  Churn-Jung Liau,et al.  Reasoning about Higher Order Uncertainty in Possiblistic Logic , 1993, ISMIS.

[2]  David Lewis Counterfactuals and Comparative Possibility , 1973 .

[3]  Didier Dubois,et al.  A Simple Modal Logic for Reasoning about Revealed Beliefs , 2009, ECSQARU.

[4]  Didier Dubois,et al.  Knowledge-Driven versus Data-Driven Logics , 2000, J. Log. Lang. Inf..

[5]  Didier Dubois,et al.  The Structure of Oppositions in Rough Set Theory and Formal Concept Analysis - Toward a New Bridge between the Two Settings , 2014, FoIKS.

[6]  Didier Dubois,et al.  Three-Valued Logics, Uncertainty Management and Rough Sets , 2014, Trans. Rough Sets.

[7]  George Lakoff,et al.  Hedges: A study in meaning criteria and the logic of fuzzy concepts , 1973, J. Philos. Log..

[8]  Steven Schockaert,et al.  Generalized possibilistic logic: Foundations and applications to qualitative reasoning about uncertainty , 2017, Artif. Intell..

[9]  Didier Dubois,et al.  A simple logic for reasoning about incomplete knowledge , 2014, Int. J. Approx. Reason..

[10]  George J. Klir,et al.  Interpretations of various uncertainty theories using models of modal logic: A summary , 1996, Fuzzy Sets Syst..

[11]  Tsau Young Lin,et al.  A Review of Rough Set Models , 1997 .

[12]  Didier Dubois,et al.  A Logic of Graded Possibility and Certainty Coping with Partial Inconsistency , 1994, UAI.

[13]  Churn-Jung Liau,et al.  Quantitative Modal Logic and Possibilistic Reasoning , 1992, ECAI.

[14]  George J. Klir,et al.  On Modal Logic Interpretation of Possibility Theory , 1994, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[15]  Tsau Young Lin,et al.  Rough Sets and Data Mining: Analysis of Imprecise Data , 1996 .

[16]  A. L. PRUF a meaning representation language for natural languages , 2008 .

[17]  Yiyu Yao,et al.  Generalization of Rough Sets using Modal Logics , 1996, Intell. Autom. Soft Comput..

[18]  Didier Dubois,et al.  Possibilistic reasoning with partially ordered beliefs , 2015, J. Appl. Log..

[19]  Janusz Zalewski,et al.  Rough sets: Theoretical aspects of reasoning about data , 1996 .

[20]  Didier Dubois,et al.  Structures of opposition induced by relations , 2015, Annals of Mathematics and Artificial Intelligence.

[21]  Donald Nute,et al.  Counterfactuals , 1975, Notre Dame J. Formal Log..

[22]  Didier Dubois,et al.  Graded cubes of opposition and possibility theory with fuzzy events , 2017, Int. J. Approx. Reason..

[23]  Didier Dubois,et al.  Possibilistic vs. Relational Semantics for Logics of Incomplete Information , 2014, IPMU.

[24]  H. Thiele Fuzzy Rough Sets versus Rough Fuzzy Sets — An Interpretation and a Comparative Study using Concepts of Modal Logics , 1998 .

[25]  Craig Boutilier,et al.  Modal logics for qualitative possibility theory , 1994, Int. J. Approx. Reason..

[26]  Lotfi A. Zadeh,et al.  Fuzzy sets and information granularity , 1996 .

[27]  G. L. S. Shackle,et al.  Decision Order and Time in Human Affairs , 1962 .

[28]  Bertrand I-Peng Lin,et al.  Proof methods for reasoning about possibility and necessity , 1993, Int. J. Approx. Reason..

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

[30]  Steven Schockaert,et al.  Stable Models in Generalized Possibilistic Logic , 2012, KR.

[31]  Luis Fariñas del Cerro,et al.  DAL - A Logic for Data Analysis , 1985, Theor. Comput. Sci..

[32]  D. Dubois,et al.  ROUGH FUZZY SETS AND FUZZY ROUGH SETS , 1990 .

[33]  Ute St. Clair,et al.  HIERARCHICAL UNCERTAINTY METATHEORY BASED UPON MODAL LOGIC , 1992 .

[34]  George J. Klir,et al.  On modal logic interpretation of Dempster–Shafer theory of evidence , 1994, Int. J. Intell. Syst..

[35]  Arie Tzvieli Possibility theory: An approach to computerized processing of uncertainty , 1990, J. Am. Soc. Inf. Sci..

[36]  Helmut Thiele Fuzzy Rough Sets versus Rough Fuzzy Sets , 1998 .

[37]  Luis Fariñas del Cerro,et al.  A Modal Analysis of Possibility Theory , 1991, ECSQARU.

[38]  Jennifer Nacht,et al.  Modal Logic An Introduction , 2016 .

[39]  D. Dubois,et al.  Twofold fuzzy sets and rough sets—Some issues in knowledge representation , 1987 .

[40]  Petr Hájek,et al.  On Modal Logics for Qualitative Possibility in a Fuzzy Setting , 1994, UAI.

[41]  Didier Dubois,et al.  The Cube of Opposition: A Structure Underlying Many Knowledge Representation Formalisms , 2015, IJCAI.

[42]  George J. Klir,et al.  On the Integration of Uncertainty Theories , 1993, Int. J. Uncertain. Fuzziness Knowl. Based Syst..

[43]  Didier Dubois,et al.  Structures of opposition induced by relations-The Boolean and the gradual cases , 2016 .

[44]  A. P. Sage,et al.  System Identification (Mathematics in Science and Engineering Series) , 1972 .

[45]  Steven Schockaert,et al.  Reasoning about Uncertainty and Explicit Ignorance in Generalized Possibilistic Logic , 2014, ECAI.

[46]  Petr Hájek,et al.  A qualitative fuzzy possibilistic logic , 1995, Int. J. Approx. Reason..

[47]  Béziau Jean-Yves New light on the Square of oppositions and its nameless corner , 2003 .

[48]  Ewa Orlowska,et al.  A logic of indiscernibility relations , 1984, Symposium on Computation Theory.

[49]  Tuan-Fang Fan,et al.  A Modal Logic for Reasoning about Possibilistic Belief Fusion , 2005, IJCAI.

[50]  Didier Dubois,et al.  From Blanché’s Hexagonal Organization of Concepts to Formal Concept Analysis and Possibility Theory , 2012, Logica Universalis.

[51]  Didier Dubois,et al.  Possibilistic logic : a retrospective and prospective view , 2003 .

[52]  Ronald Fagin,et al.  An internal semantics for modal logic , 1985, STOC '85.

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

[54]  Didier Dubois,et al.  Resolution principles in possibilistic logic , 1990, Int. J. Approx. Reason..

[55]  Andrzej Skowron,et al.  Rudiments of rough sets , 2007, Inf. Sci..

[56]  Gopalan Nadathur,et al.  Handbook of Logic in Artificial Intelligence and Logic Programming, Volume2, Deduction Methodologies , 1994, Handbook of Logic in Artificial Intelligence and Logic Programming, Volume 2.

[57]  Lotfi A. Zadeh,et al.  A Theory of Approximate Reasoning , 1979 .

[58]  Didier Dubois,et al.  Fuzzy sets and systems ' . Theory and applications , 2007 .

[59]  Didier Dubois,et al.  Structures of Opposition in Fuzzy Rough Sets , 2015, Fundam. Informaticae.

[60]  Didier Dubois,et al.  In Search of a Modal System for Possibility Theory , 1988, ECAI.

[61]  Didier Dubois,et al.  Possibilistic Logic - An Overview , 2014, Computational Logic.

[62]  Witold Lipski,et al.  On Databases with Incomplete Information , 1981, JACM.

[63]  D Dubois,et al.  Belief structures, possibility theory and decomposable confidence measures on finite sets , 1986 .

[64]  Michael Soltys Bulletin of the Section of Logic , 2002 .