Results 1 
9 of
9
Probabilistic argumentation systems
 Handbook of Defeasible Reasoning and Uncertainty Management Systems, Volume 5: Algorithms for Uncertainty and Defeasible Reasoning
, 2000
"... Different formalisms for solving problems of inference under uncertainty have been developed so far. The most popular numerical approach is the theory of Bayesian inference [42]. More general approaches are the DempsterShafer theory of evidence [51], and possibility theory [16], which is closely re ..."
Abstract

Cited by 64 (35 self)
 Add to MetaCart
(Show Context)
Different formalisms for solving problems of inference under uncertainty have been developed so far. The most popular numerical approach is the theory of Bayesian inference [42]. More general approaches are the DempsterShafer theory of evidence [51], and possibility theory [16], which is closely related to fuzzy systems.
Costbounded argumentation
 International Journal of Approximate Reasoning
"... The purpose of this paper is to present new computational techniques for probabilistic argumentation systems. It shows that instead of computing intractable large sets of arguments, it is also possible to find good approximations of the exact solutions in reasonable time. The technique presented is ..."
Abstract

Cited by 25 (14 self)
 Add to MetaCart
(Show Context)
The purpose of this paper is to present new computational techniques for probabilistic argumentation systems. It shows that instead of computing intractable large sets of arguments, it is also possible to find good approximations of the exact solutions in reasonable time. The technique presented is based on cost functions, which are used to measure the relevance of arguments.
Modelbased diagnostics and probabilistic assumptionbased reasoning
 Artificial Intelligence
, 1998
"... The mathematical foundations of modelbased diagnostics or diagnosis from first principles have been laid by Reiter [31]. In this paper we extend Reiter’s ideas of modelbased diagnostics by introducing probabilities into Reiter’s framework. This is done in a mathematically sound and precise way whi ..."
Abstract

Cited by 23 (17 self)
 Add to MetaCart
(Show Context)
The mathematical foundations of modelbased diagnostics or diagnosis from first principles have been laid by Reiter [31]. In this paper we extend Reiter’s ideas of modelbased diagnostics by introducing probabilities into Reiter’s framework. This is done in a mathematically sound and precise way which allows one to compute the posterior probability that a certain component is not working correctly given some observations of the system. A straightforward computation of these probabilities is not efficient and in this paper we propose a new method to solve this problem. Our method is logicbased and borrows ideas from assumptionbased reasoning and ATMS. We show how it is possible to determine arguments in favor of the hypothesis that a certain group of components is not working correctly. These arguments represent the symbolic or qualitative aspect of the diagnosis process. Then they are used to derive a quantitative or numerical aspect represented by the posterior probabilities. Using two new theorems about the relation between Reiter’s notion of conflict and our notion of argument, we prove that our socalled degree of support is nothing but the posterior probability that we are looking for. Furthermore, a model where each component may have more than two different operating modes is discussed and a new algorithm to compute posterior probabilities in this case is presented. Key words: Modelbased diagnostics; Assumptionbased reasoning; ATMS;
The 2SAT problem of regular signed CNF formulas
 In Proc. 30th IEEE International Symposium on MultipleValued Logic (ISMVL 2000
"... ..."
(Show Context)
ModelBased Reliability and Diagnostic: A Common Framework for Reliability and Diagnostics
 DX’02 THIRTEENTH INTERNATIONAL WORKSHOP ON PRINCIPLES OF DIAGNOSIS
, 2002
"... Technical systems are in general not guaranteed to work correctly. They are more or less reliable. One main problem for technical systems is the computation of the reliability of a system. A second main problem is the problem of diagnostic. In fact, these problems are in some sense dual to each othe ..."
Abstract

Cited by 7 (2 self)
 Add to MetaCart
Technical systems are in general not guaranteed to work correctly. They are more or less reliable. One main problem for technical systems is the computation of the reliability of a system. A second main problem is the problem of diagnostic. In fact, these problems are in some sense dual to each other. In this
Computing the Probability of Formulas Representing Events in Product Spaces
 In IPMU’98, Proceedings of the seventh international conference
, 1998
"... In this paper we present a general language for representing subsets of a product of finite sets. For example this type of language is used for representing the set of diagnoses in the general theory of modelbased diagnosis presented by Reiter [5]. In this paper it is shown that the mathematical st ..."
Abstract

Cited by 5 (3 self)
 Add to MetaCart
(Show Context)
In this paper we present a general language for representing subsets of a product of finite sets. For example this type of language is used for representing the set of diagnoses in the general theory of modelbased diagnosis presented by Reiter [5]. In this paper it is shown that the mathematical structure of a Boolean algebra is the appropriate concept to define and describe the language. After having established some general results about Boolean algebras, these results are applied in the special case of product spaces, thereby defining a language for the description of events in product spaces. Then we give two algorithms for computing the probability of a formula in the language. This problem appears for example in modelbased diagnostics when we need to compute the conditional probability of a diagnosis given the observations made on the system. 1
Building argumentation systems on set constraint logic
 Information, Uncertainty and Fusion
, 2000
"... The purpose of this paper is to show how the theory of probabilistic argumentation systems can be extended from propositional logic to the more general framework of set constraint logic. The strength of set constraint logic is that logical relations between nonbinary variables can be expressed more ..."
Abstract

Cited by 3 (2 self)
 Add to MetaCart
(Show Context)
The purpose of this paper is to show how the theory of probabilistic argumentation systems can be extended from propositional logic to the more general framework of set constraint logic. The strength of set constraint logic is that logical relations between nonbinary variables can be expressed more directly. This simplifies the classical way of modeling knowledge through propositional logic. Building argumentation systems on set constraint logic is therefore useful for improving its capabilities of expressing different forms of uncertain knowledge. 1
Eliminating Variables in General Constraint Logic
"... Drawing inferences from a set of general constraint clauses is known as a difficult problem. A general approach is based on the idea of eliminating some or all variables involved. In the particular case of propositional logic, this approach leads to a simple procedure that incorporates the wellknow ..."
Abstract
 Add to MetaCart
(Show Context)
Drawing inferences from a set of general constraint clauses is known as a difficult problem. A general approach is based on the idea of eliminating some or all variables involved. In the particular case of propositional logic, this approach leads to a simple procedure that incorporates the wellknown resolution principle. The purpose of this paper is to show how the resolution principle can be extended to constraint logic where the knowledge is given as a set of constraint clauses. The result is a general variable elimination method. The paper shows that the elimination problem can always be reduced to the problem of eliminating the variable from a (conjunctive) set of atomic constraints. Variabele elimination has a number of possible applications such as satisfiability testing, hypotheses testing, constraint solving, argumentative reasoning, and many others.
Abstract CostBounded Argumentation
"... The purpose of this paper is to present new computational techniques for probabilistic argumentation systems. It shows that instead of computing intractable large sets of arguments, it is also possible to find good approximations of the exact solutions in reasonable time. The technique presented is ..."
Abstract
 Add to MetaCart
(Show Context)
The purpose of this paper is to present new computational techniques for probabilistic argumentation systems. It shows that instead of computing intractable large sets of arguments, it is also possible to find good approximations of the exact solutions in reasonable time. The technique presented is based on cost functions, which are used to measure the relevance of arguments.