Experiences with planning for natural language generation

We investigate the application of modern planning techniques to domains arising from problems in natural language generation (NLG). In particular, we consider two novel NLGinspired planning problems, the sentence generation domain and the GIVE (“Generating Instructions in Virtual Environment”) domain, and investigate the efficiency of FF and SGPLAN in these domains. We also compare our results against an ad-hoc implementation of GraphPlan in Java. Our results are mixed. While modern planners are able to quickly solve many moderately-sized instances of our problems, the overall planning time is dominated by the grounding step that these planners perform (rather than search). This has a pronounced effect on our domains which require relatively short plans but have large universes. We share our experiences and offer these domains as challenges for the planning community.

• Type: Journal
• Year: 2011
• Where: CI
• Authors: Alexander Koller, Ronald P. A. Petrick
• Keywords: CI 2011, Modern Planning Techniques, Planning, Sentence Generation Domain