并发与概率：组合式消除混淆
Concurrency and Probability: Removing Confusion, Compositionally
AI总结：
针对Petri网中混淆与分布式决策问题，提出基于结构分支单元（s-cells）的静态分解方法，将网转换为无混淆网，使冲突备选方案可概率化，非冲突备选保持并发，且与递归停止配置对应。
摘要：
为具有混淆和分布式决策的Petri网赋予令人满意的真正并发语义是一个长期存在的问题，尤其是当人们希望通过从某个概率分布中抽取来解决决策时。这里我们提出一个通用解决方案，该方案基于对（发生）网在决策位点上的递归、静态分解，称为结构分支单元（s-cells）。每个s-cell暴露一组备选方案，称为事务。我们的解决方案将给定的Petri网转换为另一个网，其转移是s-cells的事务，其库所是原始网的库所，并带有一些用于记账的辅助结构。所得网是无混淆的，因此冲突的备选方案可以配备概率选择，而非相交的备选方案是纯粹并发的，且它们的概率分布是独立的。该构造的有效性通过与Abbes和Benveniste的递归停止配置的紧密对应得到证实。我们方法的一些优点在于：i）s-cells以组合方式静态且局部地定义；ii）我们得到的网忠实地考虑并发性。
英文摘要：
Assigning a satisfactory truly concurrent semantics to Petri nets with confusion and distributed decisions is a long standing problem, especially if one wants to resolve decisions by drawing from some probability distribution. Here we propose a general solution based on a recursive, static decomposition of (occurrence) nets in loci of decision, called structural branching cells (s-cells). Each s-cell exposes a set of alternatives, called transactions. Our solution transforms a given Petri net into another net whose transitions are the transactions of the s-cells and whose places are those of the original net, with some auxiliary structure for bookkeeping. The resulting net is confusion-free, and thus conflicting alternatives can be equipped with probabilistic choices, while nonintersecting alternatives are purely concurrent and their probability distributions are independent. The validity of the construction is witnessed by a tight correspondence with the recursively stopped configurations of Abbes and Benveniste. Some advantages of our approach are that: i) s-cells are defined statically and locally in a compositional way; ii) our resulting nets faithfully account for concurrency.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
