Algorithms in combinatorial geometry
Algorithms in combinatorial geometry
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
The complexity and approximability of finding maximum feasible subsystems of linear relations
Theoretical Computer Science
Multi party computations: past and present
PODC '97 Proceedings of the sixteenth annual ACM symposium on Principles of distributed computing
Algorithmic mechanism design (extended abstract)
STOC '99 Proceedings of the thirty-first annual ACM symposium on Theory of computing
Price and niche wars in a free-market economy of software agents
Artificial Life
Communications of the ACM
Pricing information bundles in a dynamic environment
Proceedings of the 3rd ACM conference on Electronic Commerce
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
A Theory of Learning and Generalization: With Applications to Neural Networks and Control Systems
Reputation and endorsement for web services
ACM SIGecom Exchanges - Chains of commitment
Sequential information elicitation in multi-agent systems
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Preference elicitation for interface optimization
Proceedings of the 18th annual ACM symposium on User interface software and technology
Robust mechanisms for information elicitation
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Eliciting Informative Feedback: The Peer-Prediction Method
Management Science
Mechanisms for partial information elicitation: the truth, but not the whole truth
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Partial revelation automated mechanism design
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Mechanism design with partial revelation
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
On the foundations of expected expected utility
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Complexity of mechanism design
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Robust solutions of uncertain linear programs
Operations Research Letters
Exchanging reputation information between communities: a payment-function approach
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Flexible procurement of services with uncertain durations using redundancy
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
| Hi-index | 0.00 |
We study the computational aspects of information elicitation mechanisms in which a principal attempts to elicit the private information of other agents using a carefully selected payment scheme based on proper scoring rules. Scoring rules, like many other mechanisms set in a probabilistic environment, assume that all participating agents share some common belief about the underlying probability of events. In real-life situations however, the underlying distributions are not known precisely, and small differences in beliefs of agents about these distributions may alter their behavior under the prescribed mechanism. We examine two related models for the problem. The first model assumes that agents have a similar notion of the probabilities of events, and we show that this approach leads to efficient design algorithms that produce mechanisms which are robust to small changes in the beliefs of agents. In the second model we provide the designer with a more precise and discrete set of alternative beliefs that the seller of information may hold. We show that construction of an optimal mechanism in that case is a computationally hard problem, which is even hard to approximate up to any constant. For this model, we provide two very different exponential-time algorithms for the design problem that have different asymptotic running times. Each algorithm has a different set of cases for which it is most suitable. Finally, we examine elicitation mechanisms that elicit the confidence rating of the seller regarding its information.