  In past work (Onokpasa, Wild, Wong, DCC 2023), we showed that (a) for joint
compression of RNA sequence and structure, stochastic context-free grammars are
the best known compressors and (b) that grammars which have better compression
ability also show better performance in ab initio structure prediction.
Previous grammars were manually curated by human experts. In this work, we
develop a framework for automatic and systematic search algorithms for
stochastic grammars with better compression (and prediction) ability for RNA.
We perform an exhaustive search of small grammars and identify grammars that
surpass the performance of human-expert grammars.
