Changing attitude patterns in group decision making process – a socio-technological approach

This paper proposes a novel approach to consensus reaching process, which combines a mathematical model and socio-psychological factors. We attempt to correlate two decision support systems: one with the teacher managing the process of reaching consensus within the laboratory groups of individuals, and computer-based system, with mathematical presumptions as for the consistency of the model with the reality of a particular social group

Different aspects of supporting group consensus reaching process under fuzziness

In this paper we present human-consistent approach of multi-model consensus reaching process supporting by group decision support systems. We consider the idea developed by Kacprzyk and Zadrożny [9, 10, 12] which is related to the “soft” consensus, and where the core of the system is based on fuzzy logic. Essentially, we attempt to stress the multi-model architecture of considering system and distinguish several aspects, i.e. model of agent, model of moderator, model of consensus achievement. Moreover, we present a novel concept based on fair consensus as a meaningful point of further development

Fuzzy modeling with the particle swarm optimization algorithm

The main goal of this paper is a description of clustering algorithm based on the particle swarm optimization algorithm, inspired on social behavior of animals and its application in fuzzy modeling. In the paper the idea of the heuristic swarm-based algorithm was presented, including a few modifications. Moreover, the results of the experimental evaluation were shown, both a selected optimization technique and its synthesi with a fuzzy modeling method referring to the k-means algorithm and the fuzzy control process