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Selected Methods of Combining Classifiers, when Predictions are Stored in Probability Vectors, in a Dispersed Decision-making System

Przybyła-Kasperek M.

Fundamenta Informaticae

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2016

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Vol. 147, nr 2/3

353--370

EN

Issues that are related to decision making that is based on dispersed knowledge are discussed in the paper. A dispersed decision-making system that was proposed in the earlier paper of the author is used in this paper. In the system the process of combining classifiers in coalitions is very important and negotiation is applied in the clustering process. The main aim of the article is to compare the results obtained using five different methods of conflict analysis in the system. All of these methods are used when the individual classifiers generate probability vectors over decision classes. The most popular methods are considered - a sum rule, a product rule, a median rule, a maximum rule and a minimum rule. An additional aim is to compare the results obtained with using a dispersed decision-making system with the results obtained when the prediction results are aggregated directly using the conflict analysis methods. Tests, that were performed on data from the UCI repository are presented in the paper. The best methods in a particular situation are also indicated. It was found that some methods do not generate satisfactory results when there are dummy agents in a dispersed data set. That is, there are undecided agents who assign the same probability value to many different decision values. Another conclusion was that the use of a dispersed system improves the efficiency of inference.

2

Complex Decision Systems and Conflicts Analysis Problem

Wakulicz-Deja A., Nowak-Brzezińska A., Przybyła-Kasperek M.

Fundamenta Informaticae

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2013

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Vol. 127, nr 1-4

341--356

EN

This paper discusses the issues related to the conflict analysis method and the rough set theory, process of global decision-making on the basis of knowledge which is stored in several local knowledge bases. The value of the rough set theory and conflict analysis applied in practical decision support systems with complex domain knowledge are expressed. The furthermore examples of decision support systems with complex domain knowledge are presented in this article. The paper proposes a new approach to the organizational structure of a multi-agent decision-making system, which operates on the basis of dispersed knowledge. In the presented system, the local knowledge bases will be combined into groups in a dynamic way. We will seek to designate groups of local bases on which the test object is classified to the decision classes in a similar manner. Then, a process of knowledge inconsistencies elimination will be implemented for created groups. Global decisions will be made using one of the methods for analysis of conflicts.

3

The evaluation of conflicts' degree in group decision making

Mazurek J.

Polish Journal of Management Studies

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2012

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Vol. 5

102-113

EN

In group decision making conflicts arise from the fact that individuals or groups of individuals have often different opinions about problems' solutions. These conflicts might have various degrees ranging from almost complete agreement to an absolute opposition of two equally strong sides. The aim of this article is to extend the evaluation of conflicts' degree introduced by Z. Pawlak and others originally in the rough set theory context. The scope of this generalization embraces an arbitrary number of groups or individuals involved in a conflict, an arbitrary number of their attitudes as well as different degrees of agreement or disagreement on an issue (fuzzy conflicts). The evaluation of a conflict degree is divided into two levels, as both conflict situation as a whole and each individual in a conflict can be evaluated. The proposed measures of conflicts' degree can be used in initial stages of decision making processes to the quantitative evaluation of conflict intensity, so they can provide useful information for a conflict potential resolution; and also, they might help to describe conflicts' dynamics. Numerical examples of the evaluation of conflics' degree are provided as well.

PL

W decyzjach grupowych konflikty wynikają z faktu że osoby lub grupy mają często różne opinie na temat rozwiązań problemów. Konflikty te mogą mieć różne stopnie, począwszy od pełnej zgody aż do absolutnego sprzeciwu obu stron. Celem niniejszego artykułu jest rozszerzenie oceny stopnia konfliktów wprowadzonego przez Z. Pawlaka i innych, pierwotnie w trudnym kontekście teorii mnogości. Zakres tego uogólnienia obejmuje dowolną liczbę grup lub osób zaangażowanych w konflikt, dowolną liczbę ich postaw a także różne stopnie zgodności lub niezgodności w kwestii "rozmytych konfliktów". Ocena stopnia konfliktów dzieli się na dwóch poziomach, zarówno sytuacja konfliktu jako całości jak i ocena poszczególnych osób konfliktu. Proponowane środki pomiaru stopnia konfliktu mogą być stosowane w początkowych etapach decyzyjnych do ilościowej oceny intensywności konfliktu, dzięki czemu mogą one dostarczyć użytecznych informacji dotyczących potencjalnego konfliktu a także mogą pomóc opisać dynamikę konfliktu. Zawarte zostały również numeryczne przykłady oceny stopnia konfliktu.