Reinforcement Learning

Reinforcement Learning




Reinforcement learning is the study of decision making over time with consequences. the field studies how artificial (and natural) systems learn to make decisions in complex environments based on external, and possibly delayed, feedback.

At Microsoft Research, we are working on building the theory, algorithms and systems for technology that learns from its own successes (and failures), explores the world “just enough” to learn, and can infer which decisions have led to those outcomes. Our primary goal is reinforcement learning in the real world: understanding how to build systems that work, even when simulation is unavailable and samples are scarce.

We are working to create the future across a broad range of applications, including dialogue systems, game playing, content placement, program synthesis, recommendations, web search, natural language processing, and systems optimization.

On September 24, 2018, we hosted our first annual RL Day, bringing together academia and industry to discuss a substantial breadth of reinforcement learning.

We’re also hiring! If you work on reinforcement learning or a related field, and want to build systems that change the world, please apply! We have many job opportunities across the Microsoft Research locales:

Please explore the tabs above to find more about the group, our projects and recent publications!


Research Team

Current Interns

  • Portrait of Reinforcement Learning

    Reinforcement Learning

Past Interns