Can Social Agents Efficiently Perform in Automated Negotiation?

Applied Sciences

Okan Tunalı¹  Reyhan Aydoğan²  Victor Sanchez-Anguix³  Vicente Julian⁴ 

[1] Ata Technology Platforms, 34349 Istanbul, Turkey;Computer Science, Özyeğin University, 34794 Istanbul, Turkey;Grupo de Sistemas de Optimización Aplicada, Instituto Tecnológico de Informática, Ciudad Politécnica de la Innovación, Edificio 8g, Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain;Valencian Research Institute for Artificial Intelligence (VRAIN), Universitat Politècnica de València, Camino de Vera s/n, 46022 Valencia, Spain;

关键词: automated negotiation;    intelligent agents;    multiagent systems;    agreement technologies;    heuristic negotiation;    optimization;   

DOI  :  10.3390/app11136022

来源: DOAJ

【 摘 要 】

In the last few years, we witnessed a growing body of literature about automated negotiation. Mainly, negotiating agents are either purely self-driven by maximizing their utility function or by assuming a cooperative stance by all parties involved in the negotiation. We argue that, while optimizing one’s utility function is essential, agents in a society should not ignore the opponent’s utility in the final agreement to improve the agent’s long-term perspectives in the system. This article aims to show whether it is possible to design a social agent (i.e., one that aims to optimize both sides’ utility functions) while performing efficiently in an agent society. Accordingly, we propose a social agent supported by a portfolio of strategies, a novel tit-for-tat concession mechanism, and a frequency-based opponent modeling mechanism capable of adapting its behavior according to the opponent’s behavior and the state of the negotiation. The results show that the proposed social agent not only maximizes social metrics such as the distance to the Nash bargaining point or the Kalai point but also is shown to be a pure and mixed equilibrium strategy in some realistic agent societies.

【 授权许可】

Unknown