The Michigan Internet AuctionBot: a configurable auction server for human and software agents
AGENTS '98 Proceedings of the second international conference on Autonomous agents
Commodity trading using an agent-based iterated double auction
Proceedings of the third annual conference on Autonomous Agents
An adaptive agent bidding strategy based on stochastic modeling
Proceedings of the third annual conference on Autonomous Agents
Economic dynamics of agents in multiple auctions
Proceedings of the fifth international conference on Autonomous agents
Designing Bidding Strategies for Trading Agents in Electronic Auctions
ICMAS '98 Proceedings of the 3rd International Conference on Multi Agent Systems
BiddingBot: A Multiagent Support System for Cooperative Bidding in Multiple Auctions
ICMAS '00 Proceedings of the Fourth International Conference on MultiAgent Systems (ICMAS-2000)
IJCAI'99 Proceedings of the 16th international joint conference on Artifical intelligence - Volume 1
Analysis of single and networked auctions
ACM Transactions on Internet Technology (TOIT)
Performance of Auctions and Sealed Bids
EPEW '09 Proceedings of the 6th European Performance Engineering Workshop on Computer Performance Engineering
Analysis of automated auctions
ISCIS'06 Proceedings of the 21st international conference on Computer and Information Sciences
Models of coalition formation among cooperative agents: The current state and prospects of research
Scientific and Technical Information Processing
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In the face of multiple electronic sales sites, buyers can benefit from considering multiple opportunities and devising their purchase strategy to reduce risk and increase expected utility. However, human users cannot approach and rapidly monitor multiple sites. In particular, sites where prices change dynamically such as auction sites pose a major difficulty for human concurrent activity. Even without concurrency, the majority of human users do not have the ability or the resources to compute optimal purchase decisions. Such activities can be performed by computational agents. In this paper we present mechanisms that allow agents to perform purchases on behalf of users. In particular, we devised methods that allow an agent that faces multiple dynamic sales sites to compute bids that optimized the expected utility of the user, or instead reduce and manage the risk of the purchase. The proposed mechanism are currently embedded in agents we develop in our lab.