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Mécanismes de négociation multilatérale pour la prise de décision collective

Abstract : Collective decision making is a process in which many participants with different interests interact in order to build a solution to their problem. It is inherent to many organisations and companies. Nowadays, the advances in Artificial Intelligence, notably, Multi-Agents Systems enabled the automation of decision-making processes in order to analyse and to better understand how these mechanisms work. A collective decision may be made by using a voting system or by using negotiation. In this thesis, we focus on multilateral negotiation for collective decision making by proposing negotiation models. The proposed models based on heuristic approach. The agents interact with them in order to build a solution to their problem. This context is different from models based on game theory where the set of possible solutions are supposed to be known by all agents. So heuristic negotiation issue is that agents' reasoning may be very complex. This complexity grows where the number of agents and issues to be negotiated are important. The goal of this research work consists of devising negotiation mechanisms where agents'interaction are fully decentralized. We focus on organisation aspect of the multi-agent system by using divide and conquer approach in order to reduce the negotiation complexity and hence to facilitate research of agreements. Our works tackle negotiation under different contexts which lead us to bring three contributions which focus on agents' organization, interaction protocols, negotiation object, concession strategies and effective and fair solution concept. The proposed mechanisms are implemented in JavaJade. We analyse the convergence of the negotiation, negotiation time and quality of the solution. Our models are compared with a centralized approach where all of the agents are gathered around one group to negotiate. Our empirical analyses show that our propositions allow the agents to reach collectives agreements
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Submitted on : Wednesday, February 20, 2019 - 10:05:07 AM
Last modification on : Tuesday, June 1, 2021 - 2:08:10 PM


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  • HAL Id : tel-02027250, version 1


Ndeye Arame Diago. Mécanismes de négociation multilatérale pour la prise de décision collective. Intelligence artificielle [cs.AI]. Université de Lyon; Université Cheikh Anta Diop (Dakar), 2018. Français. ⟨NNT : 2018LYSE1174⟩. ⟨tel-02027250⟩



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