2017 Poster Sessions : Naturalizing a Programming Language via Interactive Learning

Student Name : Sida Wang
Advisor : Percy Liang
Research Areas: Artificial Intelligence
Our goal is to create a convenient language interface for performing well-specified but complex actions such as analyzing data, manipulating text, and querying databases. However, existing natural language interfaces for such tasks are quite primitive compared to the power one wields with a programming language. To bridge this gap, we seed the system with a core programming language and allow users to ``naturalize'' the core language incrementally by defining alternative syntax and increasingly complex concepts in terms of compositions of simpler ones. In a voxel world, we show that a community of users can simultaneously teach one system a diverse language and use it to build 240 complex voxel structures. Over the course of three days, these builders went from using only the core language to using the full naturalized language in 74.7% of the last 10K utterances.

Sida Wang is a PhD student at Stanford working with Percy Liang and Chris Manning. He is interested in more flexible programming languages that can learn from data and adapt to its users.