Open Sourcing Active Question Reformulation with Reinforcement Learning | Code it | Scoop.it
From ai.googleblog.com - October 11, 2018 3:13 PM

Posted by Michelle Chen Huebscher, Software Engineer and Rodrigo Nogueira, New York University PhD Student and Software Engineering Intern

 

Natural language understanding is a significant ongoing focus of Google’s AI research, with application to machine translation, syntactic and semantic parsing, and much more. Importantly, as conversational technology increasingly requires the ability to directly answer users’ questions, one of the most active areas of research we pursue is question answering (QA), a fundamental building block of human dialogue.

 

Because open sourcing code is a critical component of reproducible research, we are releasing a TensorFlow package for Active Question Answering (ActiveQA), a research project that investigates using reinforcement learning to train artificial agents for question answering

 

read the entire post at https://ai.googleblog.com/2018/10/open-sourcing-active-question.html