On a concept of a consensus reaching process support system based on the use of soft computing and Web techniques

Kacprzyk, Janusz; Zadrożny, Sławomir

doi:10.1142/9789812799470_0141

Cited by 15 publications

(13 citation statements)

References 12 publications

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“…Kacprzyk and Zadro ny [21]. Among many possible linguistic summaries proposed in this context by Kacprzyk and Zadro ny [17][18][19][20]22], we employ here the following ones:…”

Section: A Discussion Guidance Using Additional Indicatorsmentioning

confidence: 99%

“…We basically employ a general framework for supporting consensus reaching due to Kacprzyk, Fedrizzi and Zadro ny [3], and Kacprzyk and Zadro ny [17] which is moderator-run with a special "superagent", a moderator. Its general, conceptual and illustrative scheme is shown in Fig.…”

Section: A General Scheme Of a Moderated Consensus Reaching Procementioning

confidence: 99%

“…, is the difference between the consensus degree for the whole set of options (10) and for the set without option i s : (17) so that it estimates the influence of a given option on the consensus degree.…”

Section: ) the Response To Exclusion Of Optionmentioning

confidence: 99%

“…There are clearly many other indicators that can be employed for the support of a moderated consensus reaching process, exemplified by Kacprzyk and Zadro ny [15][16][17][18][19][20]22], Kacprzyk, Ra and Zadro ny [23], Herrera-Viedma, Cabrerizo, Kacprzyk and Pedrycz [8] or Go u ska, Kacprzyk and Herrera-Viedma [6]. They are based on a similar philosophy of an efficiency focused approach in which the moderator works with those agents and options that either promise the highest increase of the degree of consensus or, to the contrary, cause serious problems in this respect so that should be paid a particular attention to.…”

Section: ) the Response To Exclusion Of Optionmentioning

confidence: 99%

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On efficiency-oriented support of consensus reaching in a group of agents in a fuzzy environment with a cost based preference updating approach

Gołuńska

Kacprzyk

Zadrożny

2014

2014 IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI)

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We further develop our model of consensus reaching, and its related decision support system, that is based on the concept of a soft degree of consensus proposed by Kacprzyk and Fedrizzi, the idea of fuzzy preferences, and Kacprzyk's fuzzy majority. We assume that the process of consensus reaching proceeds in a (small) group of agents (decision makers, experts,…) who express their testimonies with respect to a set of options in the form of fuzzy preferences. We develop tools and techniques to extract from those data, and from the consecutive steps (dynamics) of the consensus reaching process, some additional information which is assumed in a human consistent form of linguistic summaries that can be derived by using natural language generation (NLG). This information is meant to accelerate the consensus reaching process by pointing out to those individuals for whom the changed of testimonies, and with respect to specific pairs of options, can have the highest impact on the degree of consensus. It is therefore explicitly efficiency oriented. We assume a moderated consensus reaching process run by a specialized "super-agent", a moderator. In this paper we further extend a model and implementation of such a consensus reaching process proposed in our previous papers. We further develop linguistic tools and techniques, in the form of linguistic summaries, to help grasp relations and interplay between the agents' testimonies and their dynamics numerically analyzed by additional indicators pointing out agents and options that are most promising for the changes of preferences. We proposed a cost based scheme for the evaluation of preference updating so that the agents be not forced to change too often and too many of their preferences, which is not usually welcome by people for psychological reasons, and which should contribute to their better collaboration .

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“…Kacprzyk and Zadro ny [21]. Among many possible linguistic summaries proposed in this context by Kacprzyk and Zadro ny [17][18][19][20]22], we employ here the following ones:…”

Section: A Discussion Guidance Using Additional Indicatorsmentioning

confidence: 99%

Section: A General Scheme Of a Moderated Consensus Reaching Procementioning

confidence: 99%

Section: ) the Response To Exclusion Of Optionmentioning

confidence: 99%

Section: ) the Response To Exclusion Of Optionmentioning

confidence: 99%

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On efficiency-oriented support of consensus reaching in a group of agents in a fuzzy environment with a cost based preference updating approach

Gołuńska

Kacprzyk

Zadrożny

2014

2014 IEEE Symposium on Computational Intelligence for Human-Like Intelligence (CIHLI)

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“…And this all is practically at no additional price and effort. A more elaborate concept of a decision support system taking into account an information context of the decision making process has been proposed recently by Kacprzyk and Zadrożny [47].…”

Section: An Example: Linguistic Data Summaries To Support Sales Decismentioning

confidence: 99%

Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summaries

Kacprzyk¹,

Zadrożny²

2010

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. We present how the conceptually and numerically simple concept of a fuzzy linguistic database summary can be a very powerful tool for gaining much insight into the essence of data that may be relevant for a business activity. The use of linguistic summaries provides tools for the verbalization of data analysis (mining) results which, in addition to the more commonly used visualization e.g. via a GUI, graphical user interface, can contribute to an increased human consistency and ease of use. The results (knowledge) derived are in a simple, easily comprehensible linguistic form which can be effectively and efficiently employed for supporting decision makers via the data driven decision support system paradigm. Two new relevant aspects of the analysis are also outlined which was first initiated by the authors. First, following Kacprzyk and Zadrożny [1] comments are given on an extremely relevant aspect of scalability of linguistic summarization of data, using their new concept of a conceptual scalability that is crucial for large applications. Second, following Kacprzyk and Zadrożny [2] it is further considered how linguistic data summarization is closely related to some types of solutions used in natural language generation (NLG), which can make it possible to use more and more effective and efficient tools and techniques developed in this another rapidly developing area. An application of a computer retailer is outlined.

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A Consensus Reaching Support System Based on the Concepts of an Ideal and Anti-Ideal Agent and Option

Kacprzyk

Gołuńska²,

Zadrożny

2015

Fuzzy Technology

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On a concept of a consensus reaching process support system based on the use of soft computing and Web techniques

Cited by 15 publications

References 12 publications

On efficiency-oriented support of consensus reaching in a group of agents in a fuzzy environment with a cost based preference updating approach

On efficiency-oriented support of consensus reaching in a group of agents in a fuzzy environment with a cost based preference updating approach

Towards human consistent data driven decision support systems using verbalization of data mining results via linguistic data summaries

A Consensus Reaching Support System Based on the Concepts of an Ideal and Anti-Ideal Agent and Option

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