@inproceedings{lynch_xue_chi_2016, title={Evolving augmented graph grammars for argument analysis}, DOI={10.1145/2908961.2908994}, abstractNote={Augmented Graph Grammars are a robust rule representation for rich graph data. In this paper we present our work on the automatic induction of graph grammars for argument diagrams via EC. We show that EC outperforms the existing grammar induction algorithms gSpan and Subdue on our dataset. We also show that it is possible to augment the standard EC process to harvest a set of diverse rules which can be filtered via a post-hoc Chi-Squared analysis.}, booktitle={Proceedings of the 2016 Genetic and Evolutionary Computation Conference (GECCO'16 Companion)}, author={Lynch, C. F. and Xue, L. T. and Chi, M.}, year={2016}, pages={65–66} }