Abstract. In this paper, an agent-based evolutionary computing technique is introduced, that is geared towards the automatic induction and optimization of grammars for natural language (grael). We outline three instantiations of the grael-environment: the grael-1 system uses large annotated corpora to bootstrap grammatical structure in a society of autonomous agents, that tries to optimally redistribute grammatical information to reflect accurate probabilistic values for the task of parsing. In grael-2, agents are allowed to mutate grammatical information, effectively implementing grammar rule discovery in a practical context. Finally, by employing a separate grammar induction module at the onset of the society, grael-3 can be used as an unsupervised grammar induction technique.