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Fuzzy set and possibility theory-based methods in artificial intelligence

Didier Dubois, Henri Prade
2003 Artificial Intelligence  
First, thanks are due to the previous editors-in-chief of the journal Artificial Intelligence, Dany Bobrow and Mike Brady for their encouragements to prepare this special issue, and to the present editors-in-chief  ...  , Ray Perrault and Erik Sandewall, for their kind support.  ...  The joint use of Π and ∆ leads to a bipolar representation framework, where positive and negative information can be processed independently, yet in a coherent way [17] .  ... 
doi:10.1016/s0004-3702(03)00118-8 fatcat:plzez4jl5jafpa3yohzxcxy6cy

Possibility Theory and Its Applications: Where Do We Stand? [chapter]

Didier Dubois, Henry Prade
2015 Springer Handbook of Computational Intelligence  
Possibilistic logic provides a rich representation setting, which enables the handling of lower bounds of possibility theory measures, while remaining close to classical logic.  ...  Potential surprise is valued on a disbelief scale, namely a positive interval of the form [0, y * ], where y * denotes the absolute rejection of the event to which it is assigned.  ...  This absolute representation on an ordinal scale is slightly more expressive than the purely relational one.  ... 
doi:10.1007/978-3-662-43505-2_3 fatcat:qptvfae6hndopkvagiwlsnxaxu

A Crash Course on Generalized Possibilistic Logic [chapter]

Didier Dubois, Henri Prade
2018 Lecture Notes in Computer Science  
We offer a brief presentation of basic possibilistic logic, and of its generalisation that comes close to a modal logic albeit with simpler more natural epistemic semantics.  ...  It shows that three traditions of reasoning under or about uncertainty (setfunctions, epistemic logic and three-valued logics) can be reconciled in the setting of possibility theory.  ...  Generalized Possibilistic Logic In basic possibilistic logic, only conjunctions of possibilistic logic formulas are allowed.  ... 
doi:10.1007/978-3-030-00461-3_1 fatcat:gkxvcnah55hf3jfev4cotvhbba

Fuzzy Knowledge Representation Based on Possibilistic and Necessary Bayesian Networks [article]

Abdelkader Heni, Mohamed Nazih Omri, Adel Alimi
2012 arXiv   pre-print
The framework proposed is a possibilistic logic based one in which Bayesian nodes and their properties are represented by local necessity-valued knowledge base.  ...  In our contribution possibilistic Bayesian networks have a qualitative part and a quantitative part, represented by local knowledge bases.  ...  In our work an average fuzzy Bayesian networks is considered as a graphical representation of uncertain information.  ... 
arXiv:1206.0918v1 fatcat:574lnvk6avg75bzecghaxolhyq

Applying Maxi-adjustment to Adaptive Information Filtering Agents [article]

Raymond Lau Queensland University of Technology, Distributed Systems Technology Centre)
2000 arXiv   pre-print
In the context of adaptive information filtering, a filtering agent's beliefs about a user's information needs have to be revised regularly with reference to the user's most current information preferences  ...  In particular, the maxi-adjustment method, which follows the AGM rationale of belief change, offers a sound and robust computational mechanism to develop adaptive agents so that learning autonomy of these  ...  Acknowledgments The work reported in this paper has been funded in part by the Cooperative Research Centres Program through the Department of the Prime Minister and Cabinet of Australia.  ... 
arXiv:cs/0003014v2 fatcat:ww5s7chrfzcpvlrmhlinc56jzy

The Emergence of Fuzzy Sets: A Historical Perspective [chapter]

Didier Dubois, Henri Prade
2016 Studies in Fuzziness and Soft Computing  
in a possibilistic logic setting.  ...  The continued effort by Zadeh to apply fuzzy sets to the basic notions of a number of disciplines in computer and information sciences proved crucial in the diffusion of this concept from mathematical  ...  Inconsistency in Bipolar Information The representation capabilities of possibilistic logic can be also enlarged in the bipolar possibilistic setting [13, 9] .  ... 
doi:10.1007/978-3-319-31093-0_1 fatcat:zc63ekhuend2ddmj5tvor5m7yq

Possibilistic instance-based learning

Eyke Hüllermeier
2003 Artificial Intelligence  
Taking the possibilistic extrapolation principle as a point of departure, an instance-based learning procedure is outlined which includes the handling of incomplete information, methods for reducing storage  ...  Moreover, aspects of knowledge representation such as the modeling of uncertainty are discussed.  ...  The basic informational principle underlying the possibilistic approach to knowledge representation and reasoning is stated as a principle of minimal specificity: 4 In order to avoid any unjustified  ... 
doi:10.1016/s0004-3702(03)00019-5 fatcat:m2ud5cgdbvbyfmortzppdo3zvi

Practical Methods for Constructing Possibility Distributions

Didier Dubois, Henri Prade
2015 International Journal of Intelligent Systems  
We both consider the case of qualitative possibility theory, where the scale remains ordinal, and the case of quantitative possibility theory, where the scale is the real interval [0, 1].  ...  Methods may be order-based or similarity-based for qualitative possibility distributions, whereas statistical methods apply in the quantitative case and then possibilities encode nested random epistemic  ...  It is used in possibilistic logic. 7 However, note that the previous purely ordinal representation is less expressive than the qualitative encoding of a possibility distribution on a totally ordered  ... 
doi:10.1002/int.21782 fatcat:264gssnipbby5crdsdqi66o5ce

Possibilistic reasoning—a mini-survey and uniform semantics

Churn-Jung Liau, Bertrand I-Peng Lin
1996 Artificial Intelligence  
It is then shown that classical modal logic, conditional logic, possibilistic logic, quantitative modal logic and qualitative possibilistic logic are all sublogics of the presented logical framework.  ...  In this way, we can formalize and generalize some well-known results about possibilistic reasoning in a uniform semantics.  ...  Their suggestions lead to Section 5 and corrections of some technical errors.  ... 
doi:10.1016/s0004-3702(96)00013-6 fatcat:bbbjwpuk7vfvbkdsuv2wzv4dfa

Weighted logics for artificial intelligence – an introductory discussion

Didier Dubois, Lluís Godo, Henri Prade
2014 International Journal of Approximate Reasoning  
Yet in the scope of information storage and management, this absolute view becomes questionable.  ...  Typical graded notions One heavily entrenched tradition in AI, especially in knowledge representation and reasoning is to rely on Boolean logic.  ...  See [53] for a review of the logic-based representations of mereotopologies in classical or modal logics, and in fuzzy and rough sets settings, as well as modal logic representations of geometries.  ... 
doi:10.1016/j.ijar.2014.08.002 fatcat:hri6ffyszzernoyexdemade37m

Fuzzy-Set Based Logics — an History-Oriented Presentation of their Main Developments [chapter]

Didier Dubois, Francesc Esteva, Lluís Godo, Henri Prade
2007 Handbook of the History of Logic  
in information representation and reasoning devices.  ...  The representation of human-originated information and the formalization of commonsense reasoning has motivated different schools of research in Artificial or Computational Intelligence in the second half  ...  representation of positive and negative pieces of information.  ... 
doi:10.1016/s1874-5857(07)80009-4 fatcat:s4i5zfomgzbxnfbuif5ffsesea

Some varieties of qualitative probability [chapter]

Michael P. Wellman
1995 Lecture Notes in Computer Science  
I discuss some of these in further depth, identify central issues, and suggest some general comparisons.  ...  In this essay I present a general characterization of qualitative probability, including a partial taxonomy of possible approaches.  ...  Acknowledgment This work was supported in part by grant F49620-94-1-0027 from the US Air Force Office of Scientific Research.  ... 
doi:10.1007/bfb0035948 fatcat:kwmscel3mzai3cfmugki3ehthy

Qualitative decision theory: from savage's axioms to nonmonotonic reasoning

Didier Dubois, Hélène Fargier, Henri Prade, Patrice Perny
2002 Journal of the ACM  
It is shown that the assumption of ordinal invariance enforces a qualitative decision procedure that presupposes a comparative possibility representation of uncertainty, originally due to Lewis, and usual  ...  This paper points out some limitations of purely ordinal approaches to Savage-like decision making under uncertainty, in perfect analogy with similar difficulties in voting theory.  ...  The ordinal Savagean framework actually leads to a representation of uncertainty that is closely related to the ordering of formulas in the nonmonotonic logic ("System P") of Kraus, Lehmann and Magidor  ... 
doi:10.1145/581771.581772 fatcat:co3lytba2vaw7jptfjdyxtmami

Bipolar Representations in Reasoning, Knowledge Extraction and Decision Processes [chapter]

Didier Dubois, Henri Prade
2006 Lecture Notes in Computer Science  
They can be instrumental in logical representations of incompleteness, rule representation and extraction, argumentation, and decision analysis.  ...  This paper surveys various areas in information engineering where an explicit handling of positive and negative sides of information is appropriate. Three forms of bipolarity are laid bare.  ...  This approach can be expressed in possibilistic logic using a constraint base (containing negative information as in classical logic) and a goal base (containing positive information and behaving like  ... 
doi:10.1007/11908029_3 fatcat:biouuhpr7zd7djvn7cj3yhvkei

Reinforcement Belief Revision

Y. Jin, M. Thielscher
2008 Journal of Logic and Computation  
The capability of revising its beliefs upon new information in a rational and efficient way is crucial for an intelligent agent.  ...  The computational model for this operation allows us to assess it in terms of time and space consumption.  ...  Acknowledgments The authors are grateful to the anonymous reviewers of an earlier version of this paper for helpful comments and suggestions.  ... 
doi:10.1093/logcom/exm094 fatcat:qoda4vxx3zhyfbci2tzrrbwgsm
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