Ant Colony Systems have been widely employed in optimization issues primarily focused on path finding optimization, such as Traveling Salesman Problem. The main advantage lies in the choice of the edge to be explored, defined using the idea of pheromone. This article proposes the use of Ant Colony Systems to explore a Backus-Naur form grammar whose elements are solutions to a given problem. Similar studies, without using Ant Colonies, have been used to solve optimization problems, such as Grammatical Swarm (based on Particle Swarm Optimization) and Grammatical Evolution (based on Genetic Algorithms). Proposed algorithm opens the way to a new branch of research in Swarm Intelligence, which until now has been almost non-existent, using ant colony algorithms to solve problems described by a grammar.

中文翻译：

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群体智能模型：应用于 BNF 语法规则推导的蚁群系统

蚁群系统已被广泛用于优化问题，主要集中在寻路优化上，例如旅行商问题。主要优势在于选择要探索的边缘，使用信息素的概念定义。本文建议使用 Ant Colony Systems 来探索 Backus-Naur 形式语法，其元素是给定问题的解决方案。类似的研究，不使用蚁群，已被用于解决优化问题，例如语法群（基于粒子群优化）和语法进化（基于遗传算法）。所提出的算法为 Swarm Intelligence 的一个新研究分支开辟了道路，该分支迄今为止几乎不存在，它使用蚁群算法来解决由语法描述的问题。