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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.

This paper presents a decision support methodology for electricity market players' bilateral contract negotiations. The proposed model is based on the application of game theory, using artificial intelligence to enhance decision support method's adaptive features. This model is integrated in AiD-EM (Adaptive Decision Support for Electricity Markets Negotiations), a multi-agent system that provides electricity market players with strategic behavior capabilities to improve their outcomes from energy contracts' negotiations. Although a diversity of tools that enable the study and simulation of electricity markets has emerged during the past few years, these are mostly directed to the analysis of market models and power systems' technical constraints, making them suitable tools to support decisions of market operators and regulators. However, the equally important support of market negotiating players' decisions is being highly neglected. The proposed model contributes to overcome the existing gap concerning effective and realistic decision support for electricity market negotiating entities. The proposed method is validated by realistic electricity market simulations using real data from the Iberian market operator-MIBEL. Results show that OPEN ACCESSEnergies 2015, 8 9818 the proposed adaptive decision support features enable electricity market players to improve their outcomes from bilateral contracts' negotiations.

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The new proposal for regulating the European Internal Market for Electricity (EIME) can motivate the harmonization of the various National markets. The process of harmonizing the day-ahead markets (DAMs) is at an advanced stage, with an efficiency in the use of interconnectors of 86%. However, the harmonization of both intraday (IDMs) and balancing markets (BMs) is still in its infancy, with an efficiency in the use of interconnectors of 50 and 19%, respectively. The new proposal brings new targets to DAMs, and European countries should make efforts to comply with them. The same is true for IDMs and BMs, but involving more ambitious targets, requiring higher efforts to be accomplished. Both the analysis of the various National markets (according to their compliance with the new proposal for regulating the EIME) and the advantages of the new proposal for key market participants (particularly, consumers, variable renewable generation, and conventional generation) are presented. The analysis indicates that the proposal contributes to a potential increase of the general welfare of market participants. However, some aspects of the proposal can negatively affect the revenue obtained from the National markets, notably for variable renewable generation and conventional generation.