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Computing with words (CWW) techniques have been shown to be useful in the management of imperfect information. From the programmer's standpoint, new tools are necessary to ease the use of these techniques within current programming platforms. This paper presents a step in this direction by describing a general framework that supports the implementation of applications dealing with fuzzy objects. We pay special attention to the study of the object comparison problem by offering both a theoretical analysis and a simple and transparent way to use our theoretical results in practice.

Summary form only given. First, we briefly advocate a need of natural language based methods in data mining, notably whew domain experts have a limited knowledge of modern tools of information technology. We present some approaches to linguistic summarization of sets of (numeric and/or textual) data, and show that a fuzzy logic based approach by Yager (1982), notably in its extended and implementable version of Kacprzyk and Yager (2001), and Kacprzyk, Yager and Zadrozny (2000), offers a simplicity and intuitive appeal, in particular in its new setting by Kacprzyk and Zadrozny (2005) based on Zadeh's computing with words and protoforms.

Summary form only given. First, we briefly present the essence of some new computing paradigms that try to attain a synergy, and bridge the gap between the human user and computer systems, notably the so-called: human centric computing, human centered computing, human computing, etc. We present a brief account of modern approaches to real world decision making, emphasize the concept of a decision making process that involves more factors and aspects like: the use of explicit and tacit knowledge, intuition, individual habitual domains, non-trivial rationality, different paradigms, etc. We advocate the need for computer based decision support systems. After a short presentation of their history and classification, we indicate that decision support systems should incorporate some sort of "intelligence", and we first briefly mention some views of intelligence in an individual and collective perspective. We indicate possible advantages of using those new human-centered computing paradigms in the decision making and support context, and advocate soft computing, notably Zadeh's computing with words (and perceptions) as a tools that makes it possible to merge the ideas presented like: human centric computing, decision making processes, intelligent decision support, etc. Finally, we show an example of our own implementation of a data/document driven decision support system in which, first, Zadeh's computing with words and perceptions paradigm is employed via linguistic database summaries, elements of business intelligence and Web intelligence.

Summary form only given. We present first some general remarks on challenges faced by modern information technology, notably when a human being is a relevant factor. These challenges are mainly related to inherent difficulties in solving some "meta-problems", in particular broadly perceived decision making. We assume, on the one hand, business intelligence related perspective, augmented with elements of Web intelligence, to fully use all available tools and resources. On the other hand, we assume a human centric computing perspective in the spirit of, for instance, Dertouzos's ideas. First, we present a brief account of modem approaches to real world decision making, emphasize the concept of a decision making process that involves more factors and aspects like: the use of own and external knowledge, involvement of various ,actors, aspects, etc., individual habitual domains, non-trivial rationality, different paradigms. As an example we mention Checkland's deliberative decision making (which is an important elements of his soft approach to systems analysis). After an analysis of specifics and difficulties encountered in many real world decision-making situations, we strongly advocate the use of computer based decision support systems. First, we briefly review the history of decision support systems, and then present a popular classification, starting from data driven to Web based and inter-organizational. We indicate that decision support systems should incorporate some sort of "intelligence", and we first briefly mention some views of what intelligence may mean in this concept, and then assume some more pragmatic, though limited, view of intelligent decision support systems. We indicate possible advantages of using elements of fuzzy logic and soft computing, notably, Zadeh's computing with words to be able to somehow merge the ideas presented like: human centric computing, decision making processes, intelligent decision support, etc. Finally, we present an example of implementation in which the above-mentioned ideas have been to some extent implemented. This concern a data and document driven decision support system for a small to medium company in which, first, Zadeh's computing with words and perceptions paradigm is employed via linguistic database summaries, elements of Web intelligence are used to derive additional information, and the ideas of an intelligent decision support and human centric computing are shown to be synergistically combined. We finish with some general remarks emphasizing that fuzzy logic and soft computing, notably as exemplified by Zadeh's computing with words and perceptions may be viewed as providing just the right tools to solve the problems considered

We briefly present, first, a simple approach to derive linguistic data summaries of a set of data exemplified by "most sales are with a low commission". The approach is based on fuzzy logic with linguistic quantifiers. Then, we implement such linguistic summaries via a fuzzy querying interface to a database. We use a genetic algorithm for searching the database. We present an application for deriving relevant relations concerning sales data at a computer retailer.

We extend the basic Bellman and Zadeh's (1970) model of multistage control (decision making) in a fuzzy environment to include both objective and subjective fuzzy constraints on controls and fuzzy goals on states at the consecutive control stages. Moreover, we consider some aggregation operators to reflect different attitudes towards the satisfaction and substitutability of the fuzzy constraints and fuzzy goals. We present an extended fuzzy dynamic programming model covering those aspects. The extension is motivated by a socio-economic regional planning problem discussed in Kacprzyk and Straszak (1982, 1984), which is outlined in this paper.

We briefly survey main developments and issues related to the use of (broadly perceived) fuzzy logic in database management systems (DBMSs), in particular in database querying. We show how this can help make DBMSs and their usage easier and more human-consistent.

We propose the use of linguistic data summaries, exemplified by the proposition “most employees are young and well paid” (with a degree of validity), to grasp relevant relations in data data. We employ Yager’s (1982, 1991) concept of a linguistic data summary based on a calculus of linguistically quantified propositions. We advocate an interactive approach in that the user formulates the class of summaries of interest. We show how this is related to fuzzy database queries, and how to employ here Kacprzyk, Zadrozny—s (1994a-1997b) fuzzy querying addon, FQUERY for Access. We present an implementation for a sales database of a computer retailer.

To enhance human acceptance and hence implementability of guideline solutions provided by a decision support system, we propose some means to make decision making models to be used by the system more “human-consistent”. Basically, we try to introduce commonsense knowledge into some multicriteria and multistage (control) models. Commonsense knowledge is represented and manipulated in terms of Zadeh's fuzzy-logic-based approach, i.e. as a collection of dispositions (propositions with implicit fuzzy linguistic quantifiers).

We consider the control of a deterministic system in a fuzzy environment when the termination time is a fuzzy set T in the space of control stages T. Such a case may be adequate for some socioeconomic systems. The approach proposed is based on the idea that the grade of membership of particular t in T is regarded as a preference of that termination time (μT(t) = 1—the best one, =0—impossible) and modifies the fuzzy goal μT(r).G. Hence, one must find the best termination time t* and the maximizing decision u p ,..., ut- 1.

An idea of a new model of a Web-based system to support a group of decision makers in reaching consensus is proposed. The core of the system is a flexible human consistent representation of preferences. However many means, notably Web-based, are conceived to help a group member to form and express his or her preferences. Moreover the model integrates the mechanisms for the discussion guidance so as to smoothly and effectively run the session.

We consider the problem of group decisions, in which decision-makers have different opinions or interests. This study proposes various metric spaces for representing the movements of decision-makers for reaching consensus. We also introduce the concept of fuzzy coalition for developing an algorithm for building a feasible fuzzy coalition, which is defined as the union of winning maximum coalitions which solve the issue of consensus among decision-makers.

Among the countless papers written by Ronald R. Yager, those on Entropies and measures of information are considered, keeping in mind the notion of view of a set, in order to point out a similarity between the quantities introduced in various frameworks to evaluate a kind of entropy. We define the concept of entropy measure and we show that its main characteristic is a form of monotonicity, satisfied by quantities scrutinised by R.R. Yager.

In this chapter, a clear difference is made between the parallel design aspect and the parallel implementation aspect of evolutionary algorithms (EAs). From the algorithmic design point of view, the main parallel models for EAs are presented. A unifying view of parallel models for EAs is outlined. This chapter is organized as follows. In Sect. 55.2, the main parallel models for designing EAs are presented. Section 55.3 deals with the implementation issues of parallel EAs. In this section, the main concepts of parallel architectures and parallel programming paradigms, which interfere with the design and implementation of parallel EAs, are outlined. The main performance indicators that can be used to evaluate a parallel EAs in terms of efficiency are detailed. Finally, Sect. 55.4 deals with the design and implementation of different parallel models for EAs based on the software framework ParadisEO.

The process of intertemporal choice is intimately linked with the concept of discounting function. Usually the benchmark in this important financial tool is the instant 0. This is an actual constraint for economic agent decision-making; indeed, in many situations, individuals have to decide at instants different from 0. Obviously, this introduces a multicriteria decision making framework in which a group of agents can (or cannot) cooperate in order to obtain greater profitabilities in function of the time variable. In this financial context, it is necessary to choose between transitive and non-transitive choice, giving rise to additive and non-additive (which includes subadditive and superadditive) discounting, respectively. Finally, another classification distinguishes between discounting with increasing or decreasing impatience.

International audience; The orientation of sensors toward regions of interest of the environment is an important motor activity, monitored by ancient struc- tures of the brainstem. Particularly, the superior colliculus is known to be deeply involved in visual saccadic behavior. Target selection relies on various hints including exogenous information about the nature and the position of candidate targets and endogenous information about current motivations. We present a model of the collicular structure based on bio- logical data, the speci city of which is related to the homogeneity of the underlying substratum of computation. This makes it more suitable to process massive visual ows on a distributed architecture, as it could be requested in a realistic task in autonomous robotics. The present model is restricted to the exogenous part of the visual pathway, from the retina to the superior colliculus. A realistic behavior for the selection of exogenous targets is reported here

In this paper a face recognition/detection system is presented, composed out of three main blocks: a face extraction block, which identifies and extracts individual faces from the input image; a feature extraction block, which converts each face identified into a suitable set of features; and a PNN classifier, which recognizes the face presented to it as a feature set. Experiments carried out on a large set of images achieved excellent results in terms of speed and precision, compared with typical figures featured by most state-of-the-art systems.

When defining a term set as a (mite family of fuzzy sets on a universe of discourse, two description levels are introduced: the level of the referential and the level corresponding to the symbolic term set. Depending on the level which is privileged, two different views of reasoning with fuzzy set labels can be thought of: Zadeh’s view of approximate reasoning which takes place at the level of the universe of discourse, and another view where fuzzy sets are manipulated in a more symbolic way at the term set level, which would corresponds to the idea of computing with words recently advocated by Zadeh also. The two views are contrasted in this paper, and their differences are laid bare.