Watch as our ARM-S system autonomously stacks blocks as demonstrated on a touch based GUI!

Congratulations to Stephane for successfully defending his thesis on “Interactive Learning for Sequential Decisions and Predictions”

A copy of Stephane’s thesis is available here

Congratulations, Dr. Munoz!

June 13, 2013

Congratulations to Dan for successfully defending his thesis on “Inference Machines: Parsing Scenes via Iterated Predictions”. His thesis is available at

Read the full article →

ARM-S Project covered on the NYT

March 31, 2013

The New York Times has covered an article on the ARM-S project where we perform the task of changing a tire autonomously:  

Read the full article →

Congratulations Kris for ECCV ’12 Best Paper Honorable Mention!

October 16, 2012

Title: Activity Forecasting Authors: Kris Kitani, Brian Ziebart, Drew Bagnell and Martial Hebert Abstract: We address the task of inferring the future actions of people from noisy visual input. We denote this task activity forecasting. To achieve accurate activity forecasting, our approach models the effect of the physical environment on the choice of human actions. [...]

Read the full article →

BIRD MURI Star Wars video

September 10, 2012

The BIRD MURI team has recently published this video to showcase it’s research on autonomous avoidance of trees by micro UAVs in forests. For more information, head to the BIRD MURI page!

Read the full article →

New Arrivals!

August 20, 2012

This year we welcome Dov Katz, working with Drew Bagnell and Tony Stentz on interactive perception for manipulation in unstructured environments, Nick Rhinehart as a research programmer working on the VMR and finder projects, Andreas Wendel, a visiting PhD student from the Graz University of Technology as a visiting scholar working on the BURD MURI project [...]

Read the full article →

Congrats Kevin and Brian! ICML 2011 Best Paper Award

July 18, 2011

Computational Rationalization: The Inverse Equilibrium Problem Abstract:Modeling the purposeful behavior of imperfect agents from a small number of observations is a challenging task. When restricted to the single-agent decision-theoretic setting, inverse optimal control techniques assume that observed behavior is an approximately optimal solution to an unknown decision problem. These techniques learn a utility function that [...]

Read the full article →

Welcome to new post-doctoral fellows

July 18, 2011

Dov Katz: working with Drew Bagnell and Tony Stentz on interactive perception for manipulation in unstructured environments. Moslem Kazemi: working with Nancy Pollard and Drew Bagnell on perception and force guided manipulation. Kris Katani: working with Martial Hebert and Drew Bagnell on activity prediction. Paul Vernaza: working with Drew Bagnell on compressed information space reasoning.

Read the full article →

Preprint: A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning

March 17, 2011

Stéphane Ross Geoffrey J. Gordon J. Andrew Bagnell, Carnegie Mellon University To Appear in Proceedings of the 14th International Conference on Artificial Intelligence and Statistics (AISTATS), 2011 Link to Paper Abstract: Sequential prediction problems such as imitation learning, where future observations depend on previous predictions (actions), violate the common i.i.d. assumptions made in statistical learning. [...]

Read the full article →