An agenda-based framework for multi-issue negotiation
Artificial Intelligence
Modeling complex multi-issue negotiations using utility graphs
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
An Adaptive Bilateral Negotiation Model for E-Commerce Settings
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Predicting partner's behaviour in agent negotiation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
A spectrum of compromise aggregation operators for multi-attribute decision making
Artificial Intelligence
Approximate and online multi-issue negotiation
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
A multi-issue negotiation protocol among agents with nonlinear utility functions
Multiagent and Grid Systems - Negotiation and Scheduling Mechanisms for Multiagent Systems
Adaptive conceding strategies for automated trading agents in dynamic, open markets
Decision Support Systems
An analysis of feasible solutions for multi-issue negotiation involving nonlinear utility functions
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Multi-issue negotiation protocol for agents: exploring nonlinear utility spaces
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Pairwise issue modeling for negotiation counteroffer prediction using neural networks
Decision Support Systems
Learning to negotiate optimally in non-stationary environments
CIA'06 Proceedings of the 10th international conference on Cooperative Information Agents
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Bilateral agent negotiation is considered as a fundamental research issue in autonomous agent negotiation, and was studied well by researchers. Generally, a predefined negotiation decision function and utility function are used to generate an offer in each negotiation round according to a negotiator's negotiation strategy, preference, and restrictions. However, such a negotiation procedure may not work well when the negotiator's utility function is nonlinear, and the unique offer is difficult to be generated. That is because if the negotiator's utility function is non-monotonic, the negotiator may find several offers that come with the same utility at the same time; and if the negotiator's utility function is discrete, the negotiator may not find an offer to satisfy its expected utility exactly. In order to solve such a problem, we propose a novel negotiation model in this paper. Firstly, a 3D model is introduced to illustrate the relationships between an agent's utility function, negotiation decision function and offer generation function. Then two negotiation mechanisms are proposed to handle two types of nonlinear utility functions respectively, i.e. a multiple offer mechanism is introduced to handle non-monotonic utility functions, and an approximating offer mechanism is introduced to handle discrete utility functions. Lastly, a combined negotiation mechanism is proposed to handle nonlinear utility functions in general situations by considering both the non-monotonic and discrete. The experimental results demonstrate the effectiveness and efficiency of the proposed negotiation model.