When the information about uncertainty cannot be quantified in a simple, probabilistic way, the topic of possibilistic decision theory is often a natural one to consider. The development of possibilistic decision theory has lead to a series of possibilistic criteria, e.g pessimistic possibilistic qualitative utility, possibilistic likely dominance , binary possibilistic utility and possibilisti...

Possibilistic Defeasible Logic Programming (P-DeLP) is a logic programming language which combines features from argumentation theory and logic programming, incorporating the treatment of possibilistic uncertainty at object-language level. This paper presents a first approach towards extending P-DeLP to incorporate fuzzy constants and fuzzy propositional variables. We focus on how to characteri...

Recent research has identified the notion of indirect consistency as a rationality postulate that every rule-based argumentation frameworks should satisfy. Possibilistic Defeasible Logic Programming (PDeLP) is an argumentation framework based on logic programming which incorporates a treatment of possibilistic uncertainty at objectlanguage level, in which indirect consistency does not hold. In ...

ABSTRICT This paper uses the possibility distribution approach to estimate the insurance loss amount. A special class of parametric possibility distributions is used to model insurance loss variables. The parameters of the possibility distribution are estimated by combining statistical analysis of sample data and domain knowledge provided by actuarial experts. Insurance premiums are calculated ...

This paper introduces a novel intuitionistic fuzzy set-based heuristic algorithm of possibilistic clustering. For the purpose, some remarks on the fuzzy approach to clustering are discussed and a brief review of intuitionistic fuzzy set-based clustering procedures is given, basic concepts of the intuitionistic fuzzy set theory and the intuitionistic fuzzy generalization of the heuristic approac...

In this paper, a new method for merging multiple inconsistent knowledge bases in the framework of possibilistic logic is presented. We divide the fusion process into two steps: one is called the splitting step and the other is called the combination step. Given several inconsistent possibilistic knowledge bases (i.e. the union of these possibilistic bases is inconsistent), we split each of them...

The conventional wisdom is that the concept of information is closely related to the concept of probability. In Shannon's information theory, information is equated to a reduction in entropy—a probabilistic concept. In this paper, a different view of information is put on the table. Information is equated to restriction. More concretely, a restriction is a limitation on the values which a varia...

Auction-based electronic commerce is an increasingly interesting domain for developing trading agents. In this paper we present our first contributions towards the construction of such agents by introducing both a formal and a more pragmatical approach for the design of bidding strategies that provide buyer agents with useful heuristic guidelines to participate in auction-based tournaments. On ...

The problem of merging multiple-source uncertain information is a crucial issue in many applications. This paper proposes an analysis of possibilistic merging operators where uncertain information is encoded by means of product-based (or quantitative) possibilistic networks. We first show that the product-based merging of possibilistic networks having the same DAG structures can be easily achie...

This paper is an attempt to cast both uncertainty and time in a logical framework. It generalizes possibilistic logic, previously developed by the authors, where each classical formula is associated with a weight which obeys the laws of possibility theory. In the possibilistic temporal logic we present here, each formula is associated with a time set (a fuzzy set in the more general case) which...