Outranking-Based Interactive Exploration of a Set of Multicriteria Alternatives

Interactive procedures are very effective for exploring sets of alternatives with a view to finding the best compromise alternative. In this paper we consider the interactive exploration of implicitly or explicitly given large sets of alternatives. Upon review of classical interactive procedures, which usually assume a utility function preference model, we distinguish three typical operations used in various interactive procedures: contraction of the explored set, exploration of some neighbourhood of a current alternative and reduction of a sample of the explored set. After pointing out some areas for improvement in the traditional procedures, we describe three interactive procedures performing the three operations respectively using an outranking relation preference model. Owing to the proposed ways of building and exploiting the outranking relation, the weak points of the traditional procedures can be overcome. Finally we solve an exemplary problem using all three procedures. © 1997 John Wiley & Sons, Ltd.     

An interactive multiobjective procedure for selecting medium-term countermeasures after nuclear accidents

This paper presents a methodology for supporting medium-term decisions in the context of nuclear accidents. An interactive procedure based on a multiobjective linear model is introduced, allowing the set of feasible strategies to be explored. This procedure enables the users to express preferences on both criterion values and the structure of the strategies. Additional flexibility is provided by the possibility of integrating evolutive constraints during the decision process. © 1998 John Wiley & Sons, Ltd.     

A neural implementation of multi-adjoint logic programming

A neural net based implementation of propositional [0,1]-valued multi-adjoint logic programming is presented, which is an extension of earlier work on representing logic programs in neural networks carried out in [A.S. d'Avila Garcez et al., Neural-Symbolic Learning Systems: Foundations and Applications, Springer, 2002; S. Hölldobler et al., Appl. Intelligence 11 (1) (1999) 45–58]. Proofs of preservation of semantics are given, this makes the extension to be well-founded.The implementation needs some preprocessing of the initial program to transform it into a homogeneous program; then, transformation rules carry programs into neural networks, where truth-values of rules relate to output of neurons, truth-values of facts represent input, and network functions are determined by a set of general operators; the net outputs the values of propositional variables under its minimal model.     

题库优化设计的回顾与展望

题库优化设计是指在题库建立前确定一份最佳的题库开发蓝图,使题库更好地服务于组卷。目前,在线性计算机化测验的情景下,题库优化设计方法主要包括：线性规划法、成本函数法;在计算机适应性测验（CAT）情境下,题库设计方法主要包括：影子测验设计法、p-优化设计法。文中首先介绍这些优化设计法的基本思路、具体步骤与相关的应用研究,然后评述当前题库设计研究的局限,指出未来的可能研究方向。     

Fuzzy Logic Programming and Fuzzy Control

We show that it is possible to base fuzzy control on fuzzy logic programming. Indeed, we observe that the class of fuzzy Herbrand interpretations gives a semantics for fuzzy programs and we show that the fuzzy function associated with a fuzzy system of IF-THEN rules is the fuzzy Herbrand interpretation associated with a suitable fuzzy program.     

Applications of the MACBETH Approach in the Framework of an Additive Aggregation Model

In measurement theory terminology, MACBETH is an interactive approach for mapping into a real scale the various degrees to which the elements of a finite set possess a property P. The originality of MACBETH's questioning procedure is the possibility of establishing a constructive path towards cardinal measurement in both quantitative and substantive meaningful terms, avoiding the operational problems recognized as a weakness of other procedures. The use of the notion of semantic absolute judgements plays a key role here and the simplicity, interactivity and constructiveness of our approach insert it in the modern paradigms of decision aid. This article illustrates the usefulness of MACBETH as a tool to facilitate decision support, by describing its application in two real public decision situations where we acted as facilitators. Although the cases correspond to quite different decision contexts and problematics and our interventions have addressed diverse issues, they have in common the fact that we conducted both evaluation processes in the framework of an additive multicriteria aggregation procedure. In the first case MACBETH has been used to support the construction of (local) cardinal value functions, while the second illustrates how our approach can serve as a weighting procedure to determine the scaling constants of an additive aggregation model. © 1997 John Wiley & Sons, Ltd.