Decision procedures for multiple auctions
Proceedings of the first international joint conference on Autonomous agents and multiagent systems: part 2
Sequential Auctions for the Allocation of Resources with Complementarities
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
A Dynamic Programming Model for Algorithm Design in Simultaneous Auctions
WELCOM '01 Proceedings of the Second International Workshop on Electronic Commerce
Decision Analysis for Management Judgment
Decision Analysis for Management Judgment
Continuous value function approximation for sequential bidding policies
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Considering expected utility of future bidding options in bundle purchasing with multiple auctions
ICEC '04 Proceedings of the 6th international conference on Electronic commerce
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This paper considers the problem of making decisions in a dynamic environment where one of possibly many bundles of items must be purchased and quotes for items open and close over time. Probability measures on item prices are used when exact prices are not yet known. We show that expected utility estimation can be improved by considering how future information can affect the purchasing agent's behaviour. An efficient Monte Carlo simulation method is presented that determines the expected utility of an option in our decision tree, referred to as a QR-tree, where the number of simulations needed is linear in the size of the tree. In our experiments simulating a purchase agent in a specific market, the expected utility was estimated more than 50 times more accurately than a greedy method that always pursues the bundle with the current highest expected utility.