Evolutionary computing as a tool for grammar development

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-S can be used as an unsupervised grammar induction technique. © Springer-Verlag Berlin Heidelberg 2003.