Modeling coordination in organizations and markets
Management Science
Commodity trading using an agent-based iterated double auction
Proceedings of the third annual conference on Autonomous Agents
Distributed rational decision making
Multiagent systems
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Markov Decision Processes: Discrete Stochastic Dynamic Programming
Emergent Properties of a Market-based Digital Library with Strategic Agents
Autonomous Agents and Multi-Agent Systems
Dynamic Programming
Economic mechanism design for computerized agents
WOEC'95 Proceedings of the 1st conference on USENIX Workshop on Electronic Commerce - Volume 1
Evolutionary Negotiation in Agent-Mediated Commerce
AMT '01 Proceedings of the 6th International Computer Science Conference on Active Media Technology
A Multi-Agent Negotiation Testbed for Contracting Tasks with Temporal and Precedence Constraints
International Journal of Electronic Commerce
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The market mechanism design is important for both conventional and electronic commerce as it affects the fairness and efficiency of trading. In this paper, we propose a new market mechanism for time- constrained trading. Our mechanism mimics the traditional brokering system, where buyers and sellers meet together and negotiate through an electronic marketplace. At each time step, agents are paired up for negotiating a deal. We consider that buyer and seller agents are associated with a time constraint and a search cost, and thus must decide promptly and judiciously whether to accept an offer. One distinguishing feature of our mechanism is that the marketplace provides buyer and seller agents with statistical information about the goods. Specifically, the statistics include the probability distributions of obtaining and losing a particular offer. With this information, the agents' decision can be viewed as a Markov decision process, and the optimal (dominant) trading strategy can be computed. In other words, buyer and seller agents can make trading decisions that maximize their expected utility without the need of speculating others actions. We also explain how such a dominant strategy can be computed in an efficient manner. Another distinguishing feature of the proposed mechanism is that the statistics are updated continuously and hence the dominant trading strategy is adaptive. Experimental results verify that our mechanism facilitates a fair allocation to the trading agents under various demand and supply conditions.