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On the Difference between Merging Knowledge Bases and Combining them
, 2000
"... We investigate the logical properties of knowledge base combination operators proposed in the literature. These operators are based on the selection of some maximal subsets of the union of the knowledge bases. We argue that they are not fully satisfactory to merge knowledge bases, since the so ..."
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Cited by 43 (12 self)
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We investigate the logical properties of knowledge base combination operators proposed in the literature. These operators are based on the selection of some maximal subsets of the union of the knowledge bases. We argue that they are not fully satisfactory to merge knowledge bases, since the source of information is lost in the combination process. We show that it is the reason why those operators do not satisfy a lot of logical properties. Then we propose to use more rened selection mechanisms in order to take the distribution of information into account in the combination process. That allows to dene merging operators with a more subtle behaviour. 1 INTRODUCTION In the elds of articial intelligence and databases, one is often faced with conicting information coming from several sources. Thus, an important problem in such cases is how to reach a coherent piece of information from these contradictory ones. For example, if one wants to build an expert system from a ...
How to Infer from Inconsistent Beliefs without Revising?
 Proc. IJCAI'95
, 1995
"... This paper investigates several methods for coping with inconsistency caused by multiple source information, by introducing suitable consequence relations capable of inferring nontrivial conclusions from an inconsistent stratified knowledge base. Some of these methods presuppose a revision step, na ..."
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Cited by 38 (3 self)
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This paper investigates several methods for coping with inconsistency caused by multiple source information, by introducing suitable consequence relations capable of inferring nontrivial conclusions from an inconsistent stratified knowledge base. Some of these methods presuppose a revision step, namely a selection of one or several consistent subsets of formulas, and then classical inference is used for inferring from these subsets. Two alternative methods that do not require any revision step are studied: inference based on arguments, and a new approach called safely supported inference, where inconsistency is kept local. These two last methods look suitable when the inconsistency is due to the presence of several sources of information. The paper offers a comparative study of the various inference modes under inconsistency. 1 Introduction Inconsistency can be encountered in different reasoning tasks, in particular:  when reasoning with exceptiontolerant generic knowledge, where ...
Belief base merging as a game
 Journal of Applied NonClassical Logics
, 2004
"... ABSTRACT. We propose in this paper a new family of belief merging operators, that is based on a game between sources: until a coherent set of sources is reached, at each round a contest is organized to find out the weakest sources, then those sources has to concede (weaken their point of view). This ..."
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Cited by 15 (9 self)
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ABSTRACT. We propose in this paper a new family of belief merging operators, that is based on a game between sources: until a coherent set of sources is reached, at each round a contest is organized to find out the weakest sources, then those sources has to concede (weaken their point of view). This idea leads to numerous new interesting operators (depending of the exact meaning of “weakest ” and “concede”, that gives the two parameters for this family) and opens new perspectives for belief merging. Some existing operators are also recovered as particular cases. Those operators can be seen as a special case of Booth’s Belief Negotiation Models [BOO 02], but the achieved restriction forms a consistent family of merging operators that worths to be studied on its own.
On Structured Belief Bases
 Frontiers in Belief Revision
, 1998
"... : Most existing approaches to belief revision describe the behaviour of a highly idealized rational agent. In operations of belief change for more realistic agents, usually only a small part of an agent's beliefs is accessed at one time. This should be taken into account if we are looking for cognit ..."
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Cited by 12 (9 self)
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: Most existing approaches to belief revision describe the behaviour of a highly idealized rational agent. In operations of belief change for more realistic agents, usually only a small part of an agent's beliefs is accessed at one time. This should be taken into account if we are looking for cognitively more appropriate operations. Furthermore, it makes implementation more feasible. In this paper we show how extra structure of belief bases can be used for implementing local change as defined in [ Hansson and Wassermann, 1999 ] , where only the relevant part of an agent's beliefs is considered. Some ideas for adding structure to belief bases are presented. Structured belief bases can be seen as graphs, where each node is a belief and two nodes are adjacent if and only if they are related. We also define some notions of relatedness. 1 INTRODUCTION Intelligent agents must have some way of revising their beliefs. Even though the AGM paradigm [ Alchourr'on et al., 1985 ] provides a very el...
Ampliative Adaptive Logics and the Foundation of LogicBased Approaches to Abduction
 Logical and Computational Aspects of ModelBased Reasoning
"... In this paper, we propose a reconstruction of logicbased approaches to abductive reasoning in terms of ampliative adaptive logics. The advantages of this reconstruction are important: the resulting logics have a proper proof theory (that leads to justified conclusions even for undecidable fragm ..."
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Cited by 11 (5 self)
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In this paper, we propose a reconstruction of logicbased approaches to abductive reasoning in terms of ampliative adaptive logics. The advantages of this reconstruction are important: the resulting logics have a proper proof theory (that leads to justified conclusions even for undecidable fragments), they nicely integrate deductive and abductive steps, and they are much closer to natural reasoning than the existing systems.
Ordinal and probabilistic representations of acceptance
 J. Artificial Intelligence Research
, 2004
"... An accepted belief is a proposition considered likely enough by an agent, to be inferred from as if it were true. This paper bridges the gap between probabilistic and logical representations of accepted beliefs. To this end, natural properties of relations on propositions, describing relative streng ..."
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Cited by 11 (4 self)
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An accepted belief is a proposition considered likely enough by an agent, to be inferred from as if it were true. This paper bridges the gap between probabilistic and logical representations of accepted beliefs. To this end, natural properties of relations on propositions, describing relative strength of belief are augmented with some conditions ensuring that accepted beliefs form a deductively closed set. This requirement turns out to be very restrictive. In particular, it is shown that the sets of accepted belief of an agent can always be derived from a family of possibility rankings of states. An agent accepts a proposition in a given context if this proposition is considered more possible than its negation in this context, for all possibility rankings in the family. These results are closely connected to the nonmonotonic 'preferential' inference system of Kraus, Lehmann and Magidor and the socalled plausibility functions of Friedman and Halpern. The extent to which probability theory is compatible with acceptance relations is laid bare. A solution to the lottery paradox, which is considered as a major impediment to the use of nonmonotonic inference is proposed using a special kind of probabilities (called lexicographic, or bigstepped). The setting of acceptance relations also proposes another way of approaching the theory of belief change after the works of Gärdenfors and colleagues. Our view considers the acceptance relation as a primitive object from which belief sets are derived in various contexts. 1.
Direct Dynamic Proofs For the RescherManor Consequence Relations: The Flat Case
 Journal of Applied NonClassical Logics
, 2000
"... It was shown in [6] that the at Rescher{Manor consequence relations the Free, Strong, Argued, CBased, and Weak consequence relationare all characterized by special applications of inconsistencyadaptive logics dened from the paraconsistent logic CLuN. As as result, these consequence relations ..."
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Cited by 10 (5 self)
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It was shown in [6] that the at Rescher{Manor consequence relations the Free, Strong, Argued, CBased, and Weak consequence relationare all characterized by special applications of inconsistencyadaptive logics dened from the paraconsistent logic CLuN. As as result, these consequence relations are provided with a dynamic proof theory. In the present paper we show that the detour via an inconsistencyadaptive logic is not necessary. We present a direct dynamic proof theory, formulated in the language of Classical Logic, and prove its adequacy. 1 Aim of this Paper Rescher{Manor consequence relations constitute an approach to handling inconsistency. The underlying idea is that inconsistent sets of sentences are divided into maximal consistent subsetshenceforth MCSand that what `follows ' from the inconsistent set is dened in terms of the classical consequences of the MCS or of a selection of themClassical Logic will henceforth be abbreviated as CL. Such consequence relati...
An Adaptive Logic Based on Jaskowski's D2
, 2001
"... In this paper, I present the modal adaptive logic AJ (based on S5) as well as the discussive logic D2 r that is defined from it. D2 r is the adaptive version of Jaskowski's paraconsistent system D2. Like D2, D2 r validates all singlepremise rules of Classical Logic. However, for formulas that ..."
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Cited by 10 (4 self)
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In this paper, I present the modal adaptive logic AJ (based on S5) as well as the discussive logic D2 r that is defined from it. D2 r is the adaptive version of Jaskowski's paraconsistent system D2. Like D2, D2 r validates all singlepremise rules of Classical Logic. However, for formulas that behave consistently, D2 r moreover validates all multiplepremise rules of Classical Logic. D2 r thus leads to a consequence set that is in general much richer than that of D2. It is argued that this has clear advantages with respect to one of the main application contexts of D2, namely the interpretation of debates.
Argumentbased Expansion Operators in Possibilistic Defeasible Logic Programming: Characterization and Logical Properties
 In Proc. of ECSQARU 2005 Conference
, 2005
"... Possibilistic Defeasible Logic Programming (PDeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at objectlanguage level. ..."
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Cited by 10 (8 self)
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Possibilistic Defeasible Logic Programming (PDeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating as well the treatment of possibilistic uncertainty and fuzzy knowledge at objectlanguage level.