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Negotiation among autonomous computational agents: principles, analysis and challenges

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Abstract

Automated negotiation systems with software agents representing individuals or organizations and capable of reaching agreements through negotiation are becoming increasingly important and pervasive. Examples, to mention a few, include the industrial trend toward agent-based supply chain management, the business trend toward virtual enterprises, and the pivotal role that electronic commerce is increasingly assuming in many organizations. Artificial intelligence (AI) researchers have paid a great deal of attention to automated negotiation over the past decade and a number of prominent models have been proposed in the literature. These models exhibit fairly different features, make use of a diverse range of concepts, and show performance characteristics that vary significantly depending on the negotiation context. As a consequence, assessing and relating individual research contributions is a difficult task. Currently, there is a need to build a framework to define and characterize the essential features that are necessary to conduct automated negotiation and to compare the usage of key concepts in different publications. Furthermore, the development of such a framework can be an important step to identify the core elements of autonomous negotiating agents, to provide a coherent set of concepts related to automated negotiation, to assess progress in the field, and to highlight new research directions. Accordingly, this paper introduces a generic framework for automated negotiation. It describes, in detail, the components of the framework, assesses the sophistication of the majority of work in the AI literature on these components, and discusses a number of prominent models of negotiation. This paper also highlights some of the major challenges for future automated negotiation research.

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Lopes, F., Wooldridge, M. & Novais, A.Q. Negotiation among autonomous computational agents: principles, analysis and challenges. Artif Intell Rev 29, 1–44 (2008). https://doi.org/10.1007/s10462-009-9107-8

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