Microsoft Research Lab – Montréal

For reinforcement learning (RL), where the goal is to learn good behavior in a data-driven way, the Arcade Learning Environment (ALE), which provides access to a large number of Atari 2600 games, has been a popular test-bed.

As part of the Eighth Dialog System Technology Challenge (DSTC8), Microsoft Research and Tsinghua University are hosting a track intended to foster progress in two important aspects of dialog systems: dialog complexity and scaling to new domains. For this DSTC8…

Answering questions about a given image is a difficult task, requiring both an understanding of the image and the accompanying query. Microsoft research Montreal’s FigureQA dataset introduces a new visual reasoning task for research, specific to graphical plots and figures.…

Motivation A generation of voice assistants such as Siri, Cortana, and Google Now have been popular spoken dialogue systems. More recently, we have seen a rise in text-based conversational agents (aka chatbots). Text is preferred to voice by many users…

With massive volumes of written text being produced every second, how do we make sure that we have the most recent and relevant information available to us? Microsoft research Montreal is tackling this problem by building AI systems that can…

Microsoft TextWorld is an open-source, extensible engine that both generates and simulates text games. You can use it to train reinforcement learning (RL) agents to learn skills such as language understanding and grounding, combined with sequential decision making.