Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Algorithm for optimal winner determination in combinatorial auctions
Artificial Intelligence
Speeding Up Ascending-Bid Auctions
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A Combinatorial Auction Protocol among Versatile Experts and Amateurs
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Costly valuation computation in auctions
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
Computational-Mechanism Design: A Call to Arms
IEEE Intelligent Systems
Advantages of a leveled commitment contracting protocol
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Mechanism design with execution uncertainty
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
DFCA: a flexible refundable auction for limited capacity suppliers
GECON'07 Proceedings of the 4th international conference on Grid economics and business models
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This paper proposes an auction protocol for solving a resource allocation problem in dynamic environments. In such environments, the valuation of resources has uncertainty for each bidder, i.e., this valuation depends on the situation not only at the point when the auction is held but also at the point when the allocated resources are actually used. For example a bidder's valuation in fine weather may be different from that in rainy weather. A solution for dealing with this problem is to execute auctions whenever an event occurs and then to re-allocate resources. Re-allocating resources, however, may cause disutility. Moreover, it does not always provide an equilibrium strategy because it can be viewed as a sequential auction, which means that we cannot accurately predict what outcome will be obtained. To solve this problem, we propose an auction protocol that allows bidders to declare the cost due to re-allocation and then decides an allocation based on this cost of re-allocation as well as the surplus obtained from the allocated resources themselves in the realized situation. We prove that a bidder's truth telling is in equilibrium and that a socially efficient allocation is obtained in the proposed protocol.