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
Agent-based service composition through simultaneous negotiation in forward and reverse auctions
Proceedings of the 4th ACM conference on Electronic commerce
Efficient Monte Carlo decision tree solution in dynamic purchasing environments
ICEC '03 Proceedings of the 5th international conference on Electronic commerce
Continuous value function approximation for sequential bidding policies
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
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This paper presents an algorithm for decision-making in multiple open ascending-price (English) auctions where the buyer needs to procure a complete bundle of complementary products. When making bidding decisions, the utility of each choice is determined by considering the buyer's expected utility of future consequential decisions. The problem is modeled as a Markov decision process (MDP), and the value iteration method of dynamic programming is used to determine the value of bidding/not bidding in each state. To ease the computational burden, three state-reducing techniques are employed. When tested against adaptations of two methods from the literature, results show that the algorithm works significantly better when sufficient information on the progress of other concurrently running auctions will be available when future bidding decisions are made.