Designing Core-Selecting Payment Rules: A Computational Search Approach
42 Pages Posted: 25 May 2018 Last revised: 14 Jan 2020
Date Written: January 10, 2020
We study the design of core-selecting payment rules for combinatorial auctions (CAs), a challenging setting where no strategyproof rules exist. We show that the rule most commonly used in practice, the Quadratic rule, can be outperformed in terms of efficiency, incentives and revenue. In this paper, we present a new framework for an algorithmic search for good core-selecting rules. Within our framework, we use an algorithmic Bayes-Nash equilibrium solver to evaluate 366 rules across 30 settings to identify rules that are better than Quadratic in every dimension. We first study the well-known LLG domain and then show that our findings also generalize to the much larger and more complex LLLLGG domain. Our main finding is that our best-performing rules are Large-style rules, i.e., they provide bidders with large values with better incentives than Quadratic. Finally, we identify two particularly well-performing rules and suggest that they may be considered for practical implementation in place of Quadratic.
Keywords: Combinatorial Auctions, Payment Rules, Core
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