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Peer Neighborhood Mechanisms: A Framework for Mechanism Generalization by Richardson, Adam; Faltings, Boi is a scholarly article available to read on EtoBox.

What is Peer Neighborhood Mechanisms: A Framework for Mechanism Generalization about?

Peer prediction incentive mechanisms for crowdsourcing are generally limited to eliciting samples from categorical distributions. Prior work on extending peer prediction to arbitrary distributions has largely relied on assumptions on the structures of the distributions or known properties of the data providers. We introduce a novel class of incentive mechanisms that extend peer prediction mechanisms to arbitrary distributions by replacing the notion of an exact match with a concept of neighborhood matching. We present conditions on the belief updates of the data providers that guarantee incentive-compatibility for rational data providers, and admit a broad class of possible reasonable updates.

Author

Richardson, Adam; Faltings, Boi

Published

2023

Language

EN