Automated Multi-Attribute Negotiation with Efficient Use of Incomplete Preference Information
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 3
A Negotiation Meta Strategy Combining Trade-off and Concession Moves
Autonomous Agents and Multi-Agent Systems
Protocols for Negotiating Complex Contracts
IEEE Intelligent Systems
A multi-issue negotiation protocol among agents with nonlinear utility functions
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
The Agents' Attitudes in Fuzzy Constraint Based Automated Purchase Negotiations
CEEMAS '07 Proceedings of the 5th international Central and Eastern European conference on Multi-Agent Systems and Applications V
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A bilateral negotiation may be seen as an interaction between two agents with the goal of reaching an agreement over a given range of issues which usually involves solving a conflict of interests between the agents. Usually, the agents taking part in the negotiation will consider different issues to be the most important ones for satisfying their goals, which allows to make issue trade-offs to search for joint gains. In particular, similarity criteria have been used to perform trade-offs in bilateral negotiations. This approach behaves differently depending on the knowledge each agent has about its counterpart, and depending on the order in which the different issues are considered. In this paper we propose two new approaches to improve the search for win-win solutions, one for complete information settings and the other for incomplete information settings. The experimental evaluation shows how our proposals improve the efficiency and optimality of the negotiation process over previous approaches.