The aggregation of conflicting preferences is a central problem in multiagent systems. The key difficulty is that the agents may report their preferences insincerely. Mechanism design is the art of designing the rules of the game so that the agents are motivated to report their preferences truthfully and a (socially) desirable outcome is chosen. We propose an approach where a mechanism is automatically created for the preference aggregation setting at hand. This has several advantages, but the downside is that the mechanism design optimization problem needs to be solved anew each time. Focusing-on settings where side payments are not possible, we show that the mechanism design problem is NP-complete for deterministic mechanisms. This holds both for dominantstrategy implementation and for Bayes-Nash implementation. We then show that if we allow randomized mechanisms, the mechanism design problem becomes tractable. In other words, the coordinator can tackle the computational complexity introduced by its uncertainty the agents face additional uncertainty. This comes at no loss, and in some cases at a gain, in the (social) objective.
Complexity of Mechanism Design
Published 2002 in Conference on Uncertainty in Artificial Intelligence
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- Publication year
2002
- Venue
Conference on Uncertainty in Artificial Intelligence
- Publication date
2002-05-28
- Fields of study
Computer Science, Economics
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