Bidding Algorithms for Simultaneous Auctions: A Case Study
Autonomous Agents and Multi-Agent Systems
Bidding under uncertainty: theory and experiments
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Walverine: a Walrasian trading agent
Decision Support Systems - Special issue: Decision theory and game theory in agent design
Decision-theoretic bidding based on learned density models in simultaneous, interacting auctions
Journal of Artificial Intelligence Research
Bidding marginal utility in simultaneous auctions
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
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We study a suite of heuristics that were designed for bidding in the simultaneous auctions that characterize the Trading Agent Competition (TAC) Travel Game. At a high-level, the design of many successful TAC agents can be summarized as: (i) predict: build a model of the auctions' clearing prices, and (ii) optimize: solve for an (approximately) optimal set of bids, given this model. We focus on the optimization piece of this design.