Auctions with Severely Bounded Communication
FOCS '02 Proceedings of the 43rd Symposium on Foundations of Computer Science
Miscomputing ratio: social cost of selfish computing
AAMAS '03 Proceedings of the second international joint conference on Autonomous agents and multiagent systems
Experiments on Deliberation Equilibria in Auctions
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Costly valuation computation in auctions
TARK '01 Proceedings of the 8th conference on Theoretical aspects of rationality and knowledge
On the computational power of iterative auctions
Proceedings of the 6th ACM conference on Electronic commerce
Auction design with costly preference elicitation
Annals of Mathematics and Artificial Intelligence
Mechanism design and deliberative agents
Proceedings of the fourth international joint conference on Autonomous agents and multiagent systems
Reducing costly information acquisition in auctions
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Issues in computational Vickrey auctions
International Journal of Electronic Commerce - Special issue: Intelligent agents for electronic commerce
Towards agents participating in realistic multi-unit sealed-bid auctions
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Bidding strategies for realistic multi-unit sealed-bid auctions
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 1
Bidding strategies for realistic multi-unit sealed-bid auctions
Autonomous Agents and Multi-Agent Systems
Designing trading agents for real-world auctions
SETN'10 Proceedings of the 6th Hellenic conference on Artificial Intelligence: theories, models and applications
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In auction theory, agents are typically presumed to have perfect knowledge of their valuations. In practice, though, they may face barriers to this knowledge due to transaction costs or bounded rationality. Modeling and analyzing such settings has been the focus of much recent work, though a canonical model of such domains has not yet emerged. We begin by proposing a taxonomy of auction models with valuation uncertainty and showing how it categorizes previous work. We then restrict ourselves to single-good sealed-bid auctions, in which agents have (uncertain) independent private values and can introspect about their own (but not others') valuations through possibly costly and imperfect queries. We investigate second-price auctions, performing equilibrium analysis for cases with both discrete and continuous valuation distributions. We identify cases where every equilibrium involves either randomized or asymmetric introspection. We contrast the revenue properties of different equilibria, discuss steps the seller can take to improve revenue, and identify a form of revenue equivalence across mechanisms.