Rules of encounter: designing conventions for automated negotiation among computers
Rules of encounter: designing conventions for automated negotiation among computers
Towards a test‐bed for trading agents in electronic auction markets
AI Communications
Bilateral negotiation decisions with uncertain dynamic outside options
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Agents that react to changing market situations
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Adaptive conceding strategies for automated trading agents in dynamic, open markets
Decision Support Systems
PRIMA '09 Proceedings of the 12th International Conference on Principles of Practice in Multi-Agent Systems
Partners selection in multi-agent systems by using linear and non-linear approaches
Transactions on computational science I
Expectation of trading agent behaviour in negotiation of electronic marketplace
Web Intelligence and Agent Systems
A single issue negotiation model for agents bargaining in dynamic electronic markets
Decision Support Systems
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One of the most crucial criterion in automated negotiation is how to reach a consensus agreement for all negotiators under any negotiation environment. Currently, most negotiation strategies can work under the static environment only. This paper presents a model for designing negotiation agents that makes adjustable rates of concession by reacting to changing market situations with uncertain and dynamic outside options. This work is based on the model of market-driven agents (MDAs). To determine the amount of the concession for each trading cycle, these market-driven agents are guided by four mathematical functions of trading opportunity, trading competition, trading time and strategy and trading eagerness. The contribution of this paper is designing and developing an extended MDA model with the flexibility to respond to uncertain and dynamic outside options, so as to increase problem solving ability for agent negotiation in broad application domains.