Game Theory for Data Science: Eliciting Truthful Information - Brossura

Faltings, Boi; Radanovic, Goran

Brossura

ISBN 10: 1627057293 ISBN 13: 9781627057295

Casa editrice: Morgan & Claypool, 2017

Riassunto

Intelligent systems often depend on data provided by information agents, for example, sensor data or crowdsourced human computation. Providing accurate and relevant data requires costly effort that agents may not always be willing to provide. Thus, it becomes important not only to verify the correctness of data, but also to provide incentives so that agents that provide high-quality data are rewarded while those that do not are discouraged by low rewards.

We cover different settings and the assumptions they admit, including sensing, human computation, peer grading, reviews, and predictions. We survey different incentive mechanisms, including proper scoring rules, prediction markets and peer prediction, Bayesian Truth Serum, Peer Truth Serum, Correlated Agreement, and the settings where each of them would be suitable. As an alternative, we also consider reputation mechanisms. We complement the game-theoretic analysis with practical examples of applications in prediction platforms, community sensing, and peer grading.

Dettagli dell?edizione

• Editore: Morgan & Claypool
• Data di pubblicazione: 2017
• Lingua: Inglese
• ISBN 10: 1627057293
• ISBN 13: 9781627057295
• Rilegatura: Copertina flessibile
• Numero di pagine: 151
• Redattore: Brachman Ronald, Stone Peter
• Contatto del produttore: non disponibile
• Persona responsabile: non disponibile