Intelligent agents for automated one-to-many e-commerce negotiation
ACSC '02 Proceedings of the twenty-fifth Australasian conference on Computer science - Volume 4
Protecting Competitive Negotiation of Mobile Agents
FTDCS '99 Proceedings of the 7th IEEE Workshop on Future Trends of Distributed Computing Systems
An agenda-based framework for multi-issue negotiation
Artificial Intelligence
Bargaining with incomplete information
Annals of Mathematics and Artificial Intelligence
Specification and execution of composite trading activities
Electronic Commerce Research
Knowledge-empowered automated negotiation system for e-Commerce
Knowledge and Information Systems
A simultaneous multi-attribute soft-bargaining design for bilateral contracts
Expert Systems with Applications: An International Journal
Multi-issue negotiation with deadlines
Journal of Artificial Intelligence Research
Continuous-Time Negotiation Mechanism for Software Agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
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Negotiation is a vital component of electronic trading. It is the key decision-making approach used to reach consensus between trading partners. Generally, trading partners implement various negotiation strategies in an attempt to maximize their utilities. As strategies have impact on the outcomes of negotiation, it is imperative to have efficient negotiation strategies that truly maximize clients' utilities. In this paper, we propose a multi-attribute mobile agent-based negotiation strategy that maximizes client's utility. The strategy focuses on one-to-many bilateral negotiation. It considers different factors that significantly affect the scheduling of various negotiation phases: offer collection, evaluation, negotiation, and bid award. The factors include offers expiry time, market search space, communication delays, processing queues, and transportation times. We reasoned about the correctness of the proposed negotiation strategy with respect to the existing negotiation strategies. The analysis showed that the proposed strategy enhances client's utility, reduces negotiation time, and ensures minimum search space.