Algorithmic chemistries are often based on a fixed formalism which limits the fragment of chemistry expressible in the domain of the models. This results in limited applicability of the models in contemporary mathematical chemistry and is due to the poor fit between the logic used for model construction and the system being modeled. In this paper, I propose a system-oriented methodology which selects a formalism through a mapping of chemical transformation rules to proof-theoretic structural rules. Using a formal specification framework from the field of artificial chemistry, expressive adequacy is ensured by the choice of logic being based on the system properties to be modeled. To illustrate the methodology, a case study is provided that shows how the proposed approach selects linear logic for modeling resource sensitivity and the proof-theoretic interpretation facilitates translation to a programming language. Since the method results in a plurality of models, I conclude with a discussion on how the proposal contributes to multi-model paradigms in computational pharmacology.

中文翻译：

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算法化学的逻辑

算法化学通常基于固定的形式主义，它限制了模型领域中可表达的化学片段。这导致模型在当代数学化学中的适用性有限，并且是由于用于模型构建的逻辑与正在建模的系统之间的拟合不佳。在本文中，我提出了一种面向系统的方法，该方法通过将化学转化规则映射到证明理论结构规则来选择形式主义。使用来自人工化学领域的正式规范框架，通过基于要建模的系统属性选择逻辑来确保表达的充分性。为了说明方法论，提供了一个案例研究，展示了所提出的方法如何选择线性逻辑来建模资源敏感性，并且证明理论解释促进了向编程语言的翻译。由于该方法产生多个模型，我最后讨论了该提案如何促进计算药理学中的多模型范式。