Forecasting uncertain events with small groups
Proceedings of the 3rd ACM conference on Electronic Commerce
Extracting collective probabilistic forecasts from web games
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Computation in a distributed information market
Proceedings of the 4th ACM conference on Electronic commerce
Towards a general theory of non-cooperative computation
Proceedings of the 9th conference on Theoretical aspects of rationality and knowledge
Sequential information elicitation in multi-agent systems
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Non-cooperative computation: boolean functions with correctness and exclusivity
Theoretical Computer Science - Game theory meets theoretical computer science
The influence of variables on Boolean functions
SFCS '88 Proceedings of the 29th Annual Symposium on Foundations of Computer Science
EC '06 Proceedings of the 7th ACM conference on Electronic commerce
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We introduce a new class of mechanism design problems called prediction games. There are n self interested agents. Each agent i has a private input xi and a cost of accessing it. Given are a function f(x1, ..., xn) which predicts whether a certain event will occur and an independent distribution on the agents’ inputs. Agents can be rewarded in order to motivate them to access their inputs. The goal is to design a mechanism (protocol) which in equilibrium predicts f(.) and pays in expectation as little as possible. We investigate both, exact and approximate versions of the problem and provide several upper and lower bounds. In particular, we construct an optimal mechanism for every anonymous function and show that any function can be approximated with a relatively small expected payment.