Iterative Combinatorial Auctions: Theory and Practice
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Virtual worlds: fast and strategyproof auctions for dynamic resource allocation
Proceedings of the 4th ACM conference on Electronic commerce
Brain Meets Brawn: Why Grid and Agents Need Each Other
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
A New and Improved Design for Multiobject Iterative Auctions
Management Science
Mirage: a microeconomic resource allocation system for sensornet testbeds
EmNets '05 Proceedings of the 2nd IEEE workshop on Embedded Networked Sensors
Taming the computational complexity of combinatorial auctions: optimal and approximate approaches
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Standardizing Interactive Pricing for Electronic Business
Electronic Markets
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This paper presents an agent-based simulation environment for task scheduling in a grid. Resource allocation is performed by an iterative combinatorial auction in which proxy-bidding agents try to acquire their desired resource allocation profiles. To achieve an efficient bidding process, the auctioneer provides the bidding agents with approximated shadow prices from a linear programming formulation. The objective of this paper is to identify optimal bidding strategies in multi-agent settings with respect to varying preferences in terms of resource quantity and waiting time until bid acceptance. On the basis of a utility function we characterize two types of agents: a quantity maximizing agent with a low preference for fast bid acceptance and an impatient bidding agent with a high valuation of fast allocation of the requested resources. Bidding strategies with varying initial bid pricing and different price increments are evaluated. Quantity maximizing agents should submit initial bids with low and slowly increasing prices, whereas impatient agents should start slightly below market prices and avoid ‘overbidding'.