Distributed rational decision making
Multiagent systems
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Strategy/False-name Proof Protocols for Combinatorial Multi-Attribute Procurement Auction
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Combinatorial Auctions
A Novel Auction Mechanism for Selling Time-Sensitive E-Services
CEC '05 Proceedings of the Seventh IEEE International Conference on E-Commerce Technology
Multiagent resource allocation
The Knowledge Engineering Review
Honesty and trust revisited: the advantages of being neutral about other's cognitive models
Autonomous Agents and Multi-Agent Systems
Fairness in multi-agent systems
The Knowledge Engineering Review
Recurrent auctions in e-commerce
Recurrent auctions in e-commerce
A Short Introduction to Computational Social Choice
SOFSEM '07 Proceedings of the 33rd conference on Current Trends in Theory and Practice of Computer Science
A Fair Mechanism for Recurrent Multi-unit Auctions
MATES '08 Proceedings of the 6th German conference on Multiagent System Technologies
Thirteen Reasons Why the Vickrey-Clarke-Groves Process Is Not Practical
Operations Research
Auction Mechanisms for Efficient Advertisement Selection on Public Displays
Proceedings of the 2006 conference on ECAI 2006: 17th European Conference on Artificial Intelligence August 29 -- September 1, 2006, Riva del Garda, Italy
Negotiating socially optimal allocations of resources
Journal of Artificial Intelligence Research
On fairness and learning agents in a bargaining model with uncertainty
Cognitive Systems Research
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Auctions have been used to deal with resource allocation in multiagent environments, especially in service-oriented electronic markets. In this type of market, resources are perishable and auctions are repeated over time with the same or a very similar set of agents. In this scenario it is advisable to use recurrent auctions: a sequence of auctions of any kind where the result of one auction may influence the following one. Some problems do appear in these situations, as for instance, the bidder drop problem, the asymmetric balance of negotiation power or resource waste, which could cause the market to collapse. Fair mechanisms can be useful to minimize the effects of these problems. With this aim, we have analyzed four previous fair mechanisms under dynamic scenarios and we have proposed a new one that takes into account changes in the supply as well as the presence of alternative marketplaces. We experimentally show how the new mechanism presents a higher average performance under all simulated conditions, resulting in a higher profit for the auctioneer than with the previous ones, and in most cases avoiding the waste of resources. © 2012 Wiley Periodicals, Inc.