A Multiagent Approach for Collective Decision Making in Knowledge Management

Autor: Imène Brigui-Chtioui, Inès Saad
Přispěvatelé: emlyon business school, business school, emlyon
Jazyk: angličtina
Rok vydání: 2011
Předmět:
Argumentative
Decision support system
Knowledge management
Computer science
Strategy and Management
0211 other engineering and technologies
General Decision Sciences
02 engineering and technology
Variation (game tree)
Conflict resolution
Argumentation theory
Arts and Humanities (miscellaneous)
Management of Technology and Innovation
Argumentation
0202 electrical engineering
electronic engineering
information engineering
[SHS.ECO] Humanities and Social Sciences/Economics and Finance
021103 operations research
Management science
business.industry
Multi-agent system
Multi-agent systems
General Social Sciences
Resolution (logic)
[SHS.ECO]Humanities and Social Sciences/Economics and Finance
Group decision-making
[SHS.GESTION]Humanities and Social Sciences/Business administration
020201 artificial intelligence & image processing
knowledge classification
[SHS.GESTION] Humanities and Social Sciences/Business administration
business
Zdroj: Group Decision and Negotiation
Group Decision and Negotiation, 2011, 19-37 p
ISSN: 0926-2644
Popis: International audience; In this paper we propose an argumentative multiagent model based on a mediator agent in order to automate the resolution of conflicts between decision makers for identifying knowledge that need to be capitalized and that we call “crucial knowledge”. We follow both an argumentative approach and a multi-agent system based on a mediator agent. This new approach allows the mediator agent to elicit preference of decision makers which can be different or even contradictory while exploiting and managing their multiple points of view to identify crucial knowledge. Concrete experiments have been conducted on real data from an automotive company and on randomly generated data. We have observed that a non-argumentative approach is more sensitive to the variation of the number of knowledge than an argumentative one. Indeed, the classification results using the multiagent system are consistent with classifications of human decision makers in nearly 80% of studied cases.
Databáze: OpenAIRE
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