In this paper we present some results obtained with a troupe of low-cost robots designed to cooperatively explore and adquire the map of unknown structured orthogonal environments. In order to improve the covering of the explored zone, the robots show different behaviours and cooperate by transferring each other the perceived environment when they meet. The returning robots deliver to a host co...

The use of positive and negative reasons in inference and decision aiding is a recurrent issue of investigation as far as the type of formal language to use within a DSS is concerned. A language enabling to explicitly take into account such reasons is Belnap's logic and the four valued logics derived from it. In this paper, we explore the interpretation of a continuous extension of a four value...

The difference between Bayesian conditioning and Lewis' imaging is somewhat similar to the one between Gardenfors' belief revision and Katsuno and Mendelzon' updating in the logical framework. Counterparts in possibility theory of these two operations are presented, including the case of conditioning upon an uncertain observation. Possibilistic conditioning satisfies all the postulates for beli...

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...

This paper proposes a model for Information Retrieval (IR) based on possibilistic directed networks. Relations documents-terms and query-terms are modeled through possibility and necessity measures rather than a probability measure. The relevance value for the document given the query is measured by two degrees: the necessity and the possibility. More precisely, the user’s query triggers a prop...

It is well known that the theory of probability can be treated and developed in a consistent and uniform way using the classical theory of measure and integration. Indeed, the Russian scientist Kolmogorov identified probability with normalized classical measures and used the Lebesgue theory of integration to give a logically consistent and unifying account of probability theory. In this paper, ...

A new method that aims to automatically classify a set of objects in spite of the imperfection and the uncertainty of their heterogeneously-assigned data is proposed in this paper. This method is based essentially on possibility theory to estimate the similarity among the objects, and on belief theory and multidimensional scaling methods to construct the compatible evidential class partition. T...

1. Gradualness: the idea that many categories in natural language are a matter of degree, including truth. The extension of a gradual predicate is a fuzzy set, a set where the transition between membership and non-membership is gradual rather than abrupt. This is Zadeh’s original intuition [29]. 2. Epistemic Uncertainty: the idea of partial or incomplete information. In its most primitive form,...

This paper is a first step in laying down a theoretical foundation for asset allocation under uncertainty, based on possibility theory. First, fuzzy financial knowledge representation is treated. Then, some issues relevant to financial decision making are approached from the standpoint of possibility theory.

Type-2 (T2) fuzzy variable is an extension of an ordinary fuzzy variable. In fuzzy possibility theory, T2 fuzzy variable is defined as a measurable map from the universe to the set of real numbers, and the possibility of a T2 fuzzy variable takes on a real number is a regular fuzzy variable (RFV). T2 fuzziness, which is usually used to handle linguistic uncertainties, can be described as T2 fuz...