Abstract

Formal grammars, studied by N. Chomsky for the definition of equivalence with languages and models of computing, have been a useful tool in the development of compilers, programming languages, natural language processing, automata theory, etc. The words or symbols of these formal languages can denote deduced actions that correspond to specific behaviors of a robotic entity or agent that interacts with an environment. The primary objective of this paper pretend to represent and generate simple behaviors of artificial agents. Reinforcement learning techniques, grammars, and languages, as defined based on the model of the proposed system were applied to the typical case of the ideal route on the problem of artificial ant. The application of such techniques proofs the viability of building robots that might learn through interaction with the environment.