Biography

Georges Konidaris is an Assistant Professor of Computer Science at Brown. Before joining Brown, he was on the faculty at Duke, and a postdoctoral researcher at MIT. George holds a PhD in Computer Science from the University of Massachusetts Amherst, an MSc in Artificial Intelligence from the University of Edinburgh, and a BScHons in Computer Science from the University of the Witwatersrand. He is the recent recipient of Young Faculty Awards from DARPA and the AFOSR.

Abstract

Learning Abstract Models for Symbolic High-Level Planning

The key challenge is designing intelligent robots is abstraction. Generally capable behavior requires high-level reasoning and planning, but perception and actuation must ultimately be performed using noisy, high-bandwidth, low-level sensors and effectors. I will describe recent research that investigates the link between procedural abstraction (in the form of motor skills) and state abdstraction. I will present results establishing a link between the skills available to a robot and the abstract representations it should use to plan with them; I will then describe an example of a robot autonomously learning an abstract representation directly from sensorimotor data, and then using it to plan.