This paper discusses a multi-objective portfolio optimization problem for practical portfolio selection in fuzzy environment, in which the return rates and the turnover rates are characterized by fuzzy variables. Based on the possibility theory, fuzzy return and liquidity are quantified by possibilistic mean, and market risk and liquidity risk are measured by lower possibilistic semivariance. T...

Possibilistic linear equality systems (PLES) are linear equality systems with fuzzy parameters and crisp variables. We study the problem: For a given PLES with weakly noninteractive fuzzy number parameters how does the solution change if the parameters are varied?

Linear systems with fuzzy parameters and crisp variables defined by the Zadehs extension principle are called possibilistic linear systems. The purpose of this paper is to outline some properties of these systems.

Possibilistic logic bases and possibilistic graphs are two different frameworks of interest for representing knowledge. The former ranks the pieces of knowledge (expressed by logical formulas) according to their level of certainty, while the latter exhibits relationships between variables. The two types of representation are semantically equivalent when they lead to the same possibility distrib...

Possibilistic and qualitative POMDPs (πPOMDPs) are counterparts of POMDPs used to model situations where the agent’s initial belief or observation probabilities are imprecise due to lack of past experiences or insufficient data collection. However, like probabilistic POMDPs, optimally solving πPOMDPs is intractable: the finite belief state space exponentially grows with the number of system’s s...

To address the need for efficient and unbiased experimental testing of methods for decision under uncertainty, we devise an approach for probing weaknesses of these methods by running numerical experiments on readily available or easily obtainable databases of real life data. Since the approach uses real life data, it allows us to study the effect of modeling error on the performance of a metho...

Possibilistic knowledge bases gather propositional formulas associated with degrees belonging to a linearly ordered scale. These degrees reflect certainty or priority, depending if the formulas encode pieces of beliefs or goals to be pursued. Possibilistic logic provides a simple format that turns to be useful for handling qualitative uncertainty, exceptions or preferences. The main result of t...

In this paper we will summarize some normative properties of possibility distributions. 1 Probability and Possibility In 2001 Carlsson and Fullér [1] introduced the possibilistic mean value, variance and covariance of fuzzy numbers. In 2003 Fullér and Majlender [4] introduced the notations of crisp weighted possibilistic mean value, variance and covariance of fuzzy numbers, which are consistent...

The paper discusses the use of product-based possibilistic networks for representing conditional preference statements on discrete variables. The approach uses non-instantiated possibility weights to define conditional preference tables. Moreover, additional information about the relative strengths of symbolic weights can be taken into account. It yields a partial preference order among possibl...

We introduce the class of possibilistic nested logic programs. These possibilistic logic programs allow us to use nested expressions in the bodies and the heads of their rules. By considering a possibilistic nested logic program as a possibilistic theory, a construction of a possibilistic logic programing semantics based on answer sets for nested logic programs and the proof theory of possibili...