George KonidarisDirector: Intelligent Robot Lab
Department of Computer Science
Brown University, Providence RI
My research aims to build intelligent, autonomous, general-purpose robots that are generally capable in a wide variety of tasks and environments.
I focus on understanding how to design agents that learn abstraction hierarchies that enable fast, goal-oriented planning. I develop and apply techniques from machine learning, reinforcement learning, optimal control and planning to construct well-grounded hierarchies that result in fast planning for common cases, and are robust to uncertainty at every level of control.
I believe that it will take advances in all of these areas, and additionally advances in how to integrate these areas, to solve the AI problem.
This video of some of my recent work is a good indicator of my interests - it combines ideas from hierarchical reinforcement learning, probabilistic machine learning, task-level planning, and robotics to create a robot that autonomously learns an abstract symbolic model of an environment and then uses it to plan:
Here are a few sample project pages:
I am currently teaching:
I have previously taught the following classes at Brown:
I taught the following classes when I was at Duke: