A Market-Inspired Bidding Scheme for Peer Review Paper Assignment

Authors

  • Reshef Meir Technion, Israel
  • Jérôme Lang Université Paris Dauphine, France
  • Julien Lesca Université Paris Dauphine, France
  • Nicholas Mattei Tulane University, LA, USA
  • Natan Kaminsky Technion, Israel

DOI:

https://doi.org/10.1609/aaai.v35i6.16609

Keywords:

AI for Conference Organization and Delivery (AICOD), Mechanism Design, Social Choice / Voting

Abstract

We propose a market-inspired bidding scheme for the assignment of paper reviews in large academic conferences. We provide an analysis of the incentives of reviewers during the bidding phase, when reviewers have both private costs and some information about the demand for each paper; and their goal is to obtain the best possible k papers for a predetermined k. We show that by assigning `budgets' to reviewers and a `price' for every paper that is (roughly) proportional to its demand, the best response of a reviewer is to bid sincerely, i.e., on her most favorite papers, and match the budget even when it is not enforced. This game-theoretic analysis is based on a simple, prototypical assignment algorithm. We show via extensive simulations on bidding data from real conferences, that our bidding scheme would substantially improve both the bid distribution and the resulting assignment.

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Published

2021-05-18

How to Cite

Meir, R., Lang, J., Lesca, J., Mattei, N., & Kaminsky, N. (2021). A Market-Inspired Bidding Scheme for Peer Review Paper Assignment. Proceedings of the AAAI Conference on Artificial Intelligence, 35(6), 4776-4784. https://doi.org/10.1609/aaai.v35i6.16609

Issue

Section

AAAI Technical Track Focus Area on AI for Conference Organization and Delivery