基于Shapley值的区块链私密交易撮合收益再分配方法
Shapley Value-based Approach for Redistributing Revenue of Matchmaking of Private Transactions in Blockchains
AI总结：
本研究针对区块链MEV场景下私密交易撮合的收益再分配问题，基于合作博弈论定义RST-Game，提出用其Shapley值实现公平分配，因问题复杂度高设计了近似计算的随机算法并验证有效。
摘要：
在区块链场景中，MEV（最大可提取价值）指通过在区块生产中纳入、排除或重新排序交易可提取的最大价值。搜索者通常参与订单流拍卖（OFA），以获取私密交易的独家权限，这类交易由被称为撮合者（也叫订单流提供者，OFP）的实体提供。多数情况下，将此类拍卖产生的收益在交易创建者之间再分配是合理的。本研究正式提出了MEV中的撮合问题、其理想特性及相关挑战。我们运用合作博弈论，将撮合场景下的公平收益再分配概念形式化，并阐述了其潜在的可能性与不可能性。具体而言，我们为交易创建者定义了一种特征形式博弈，称为RST-Game。我们提出利用RST-Game的Shapley值进行收益再分配。研究表明，对应的问题复杂度可能属于SUBEXP（即$2^{o(n)}$，其中$n$为交易数量），因此有必要对Shapley值进行近似计算。此外，我们提出了一种用于计算RST-Game中Shapley值的随机算法，并通过实验验证了其有效性。
英文摘要：
In the context of blockchain, MEV refers to the maximum value that can be extracted from block production through the inclusion, exclusion, or reordering of transactions. Searchers often participate in order flow auctions (OFAs) to obtain exclusive rights to private transactions, available through entities called matchmakers, also known as order flow providers (OFPs). Most often, redistributing the revenue generated through such auctions among transaction creators is desirable. In this work, we formally introduce the matchmaking problem in MEV, its desirable properties, and associated challenges. Using cooperative game theory, we formalize the notion of fair revenue redistribution in matchmaking and present its potential possibilities and impossibilities. Precisely, we define a characteristic form game, referred to as RST-Game, for the transaction creators. We propose to redistribute the revenue using the Shapley value of RST-Game. We show that the corresponding problem could be SUBEXP (i.e. $2^{o(n)}$, where $n$ is the number of transactions); therefore, approximating the Shapley value is necessary. Further, we propose a randomized algorithm for computing the Shapley value in RST-Game and empirically verify its efficacy.
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