ACORD: Ant Colony Optimization and BNF grammar rule derivation. Ant Colony Systems have been widely employed in optimization issues primarily focused on path finding optimization, such as Travelling Salesman problem. The first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. Besides, ant colony optimization algorithms have been applied to many combinatorial optimization problems, ranging from quadratic assignment to protein folding or routing vehicles and a lot of derived methods have been adapted to dynamic problems in real variables, stochastic problems, multi-targets and parallel implementations. 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. (All source code in (mathrm{R}) is available at url{}).