Home/J. Andrew (Drew) Bagnell

J. Andrew (Drew) Bagnell

Associate Professor
Email: bagnell2@andrew.cmu.edu
Office: NSH 3113
Personal Homepage
Administrative Assistant: Jessica Butterbaugh

I am interested in “closing the loop” on complex systems; that is, I am interested in designing algorithms that allow systems to observe their own operation and improve performance. My belief is that the border land between planning, control and computational learning is particularly rich with research challenges and potential to make real, immediate impact on applications. I’m particularly interested in systems for which we can obtain at best a partial model. To this end, I’m excited about extending research tools that come from information theory, statistics, control theory, statistical physics and optimization.

At the moment, I am particularly focused on two areas in machine learning. First I am working on applications of learning and decision making applied to mobile robotics. Second, I am interested in developing rich, structured probabilistic models that are appropriate for both making and learning decisions.

Publications

Displaying 150 Publications
A Probabilistic Planning Framework for Planar Grasping Under Uncertainty
Jiaji Zhou, Robert Paolini, Aaron M. Johnson, J. Andrew (Drew) Bagnell, Matthew T. Mason

2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017), September, 2017

A Fast Stochastic Contact Model for Planar Pushing and Grasping: Theory and Experimental Validation
Jiaji Zhou, J. Andrew (Drew) Bagnell, Matthew T. Mason

Robotics: Science and Systems, July, 2017

Gradient Boosting on Stochastic Data Streams
Hanzhang Hu, Wen Sun, Arun Venkatraman, Martial Hebert, J. Andrew (Drew) Bagnell

International Conference on Artificial Intelligence and Statistics (AISTATS 2017), April, 2017

Deeply AggreVaTeD: Differentiable Imitation Learning for Sequential Prediction
Wen Sun, Arun Venkatraman, Geoffrey J. Gordon, Byron Boots, J. Andrew (Drew) Bagnell

CMU-RI-TR-17-05, March, 2017

A Discriminative Framework for Anomaly Detection in Large Videos
Allison Del Giorno, J. Andrew (Drew) Bagnell, Martial Hebert

European Conference on Computer Vision (ECCV), No. 2016, October, 2016

A Discriminative Framework for Anomaly Detection in Large Videos
Allison Del Giorno, J. Andrew (Drew) Bagnell, Martial Hebert

European Conference on Computer Vision (ECCV), October, 2016

Improved Learing of Dynamics for Control
Arun Venkatraman, Roberto Capobianco, Lerrel Pinto, Martial Hebert, Daniele Nardi, J. Andrew (Drew) Bagnell

International Symposium on Experimental Robotics, October, 2016

Improved Learing of Dynamics for Control
Arun Venkatraman, Roberto Capobianco, Lerrel Pinto, Martial Hebert, Daniele Nardi, J. Andrew (Drew) Bagnell

International Symposium on Experimental Robotics, October, 2016

Inference Machines for Nonparametric Filter Learning
Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew (Drew) Bagnell

25th International Joint Conference on Artificial Intelligence (IJCAI-16), July, 2016

Inference Machines for Nonparametric Filter Learning
Arun Venkatraman, Wen Sun, Martial Hebert, Byron Boots, J. Andrew (Drew) Bagnell

25th International Joint Conference on Artificial Intelligence (IJCAI-16), July, 2016

Introspective Perception: Learning to Predict Failures in Vision Systems
Shreyansh Daftry, Sam Zeng, J. Andrew (Drew) Bagnell, Martial Hebert

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), July, 2016

Introspective Perception: Learning to Predict Failures in Vision Systems
Shreyansh Daftry, Sam Zeng, J. Andrew (Drew) Bagnell, Martial Hebert

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2016), July, 2016

Learning to Filter with Predictive State Inference Machines
Wen Sun, Arun Venkatraman, Byron Boots, and J. Andrew (Drew) Bagnell

International Conference on Machine Learning (ICML 2016), June, 2016

Learning to Smooth with Bidirectional Predictive State Inference Machines
Wen Sun, Roberto Capobianco, Geoffrey Gordon, J. Andrew (Drew) Bagnell, Byron Boots

The Conference on Uncertainty in Artificial Intelligence (UAI 2016), June, 2016

A Convex Polynomial Force-Motion Model for Planar Sliding: Identification and Application
Jiaji Zhou, Robert Paolini, J. Andrew (Drew) Bagnell, Matthew T. Mason

International Conference on Robotics and Automation (ICRA) 2016, May, 2016

Online Bellman Residual and Temporal Difference Algorithms with Predictive Error Guarantees
Wen Sun, J. Andrew (Drew) Bagnell

The 25th International Joint Conference on Artificial Intelligence - IJCAI 2016, April, 2016

Robust Monocular Flight in Cluttered Outdoor Environments
Shreyansh Daftry, Sam Zeng, Arbaaz Khan, Debadeepta Dey, Narek Melik-Barkhudarov, J. Andrew (Drew) Bagnell, Martial Hebert

ArXiv, April, 2016

Blending of brain-machine interface and vision-guided autonomous robotics improves neuroprosthetic arm performance during grasping
John E. Downey, Jeffrey M. Weiss, Katharina Muelling, Arun Venkatraman, Jean-Sebastien Valois, Martial Hebert, J. Andrew (Drew) Bagnell, Andrew B. Schwartz, Jennifer L. Collinger

Journal of Neuro Engineering and Rehabilitation, Vol. 13, No. 1, March, 2016

Online Instrumental Variable Regression with Applications to Online Linear System Identification
Arun Venkatraman, Wen Sun, Martial Hebert, J. Andrew (Drew) Bagnell, Byron Boots

Thirtieth AAAI Conference on Artificial Intelligence (AAAI-16), February, 2016

Learning Positive Functions in a Hilbert Space
J. Andrew (Drew) Bagnell and Amir-massoud Farahmand

NIPS Workshop on Optimization, (OPT2015), December, 2015

Autonomy Infused Teleoperation with Application to BCI Manipulation
Katharina Muelling, Arun Venkatraman, Jean-Sebastien Valois, John Downey, Jeffrey Weiss, Shervin Javdani, Martial Hebert, Andrew B. Schwartz, Jennifer L. Collinger and J. Andrew (Drew) Bagnell

Proceedings of Robotics: Science and Systems, July, 2015

Online Bellman Residual Algorithms with Predictive Error Guarantees
Wen Sun and J. Andrew (Drew) Bagnell

The 31st Conference on Uncertainty in Artificial Intelligence (UAI), July, 2015

Shared Autonomy via Hindsight Optimization
Shervin Javdani, Siddhartha Srinivasa and J. Andrew (Drew) Bagnell

Proceedings of Robotics: Science and Systems, July, 2015

Theoretical Limits of Speed and Resolution for Kinodynamic Planning in a Poisson Forest
Sanjiban Choudhury, Sebastian Scherer and J. Andrew (Drew) Bagnell

Robotics Science and Systems, July, 2015

Vision and Learning for Deliberative Monocular Cluttered Flight
Debadeepta Dey, Kumar Shaurya Shankar, Sam Zeng, Rupesh Mehta, M. Talha Agcayazi, Christopher Eriksen, Shreyansh Daftry, Martial Hebert and J. Andrew (Drew) Bagnell

Field and Service Robotics (FSR), June, 2015

Movement Primitives via Optimization
Anca Dragan, Katharina Muelling, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

International Conference on Robotics and Automation (ICRA), May, 2015

Semi-Dense Visual Odometry for Monocular Navigation in Cluttered Environment
Shreyansh Daftry, Debadeepta Dey, Harsimrat Sandhawalia, Sam Zeng, J. Andrew (Drew) Bagnell and Martial Hebert

IEEE International Conference on Robotics and Automation (ICRA) workshop on Recent Advances in Sensing and Actuation for Bioinspired Agile Flight, May, 2015

Visual Chunking: A List Prediction Framework for Region-Based Object Detection
Nicholas Rhinehart, Jiaji Zhou, Martial Hebert and J. Andrew (Drew) Bagnell

IEEE International Conference on Robotics and Automation (ICRA), May, 2015

A Unified View of Large-scale Zero-sum Equilibrium Computation
Kevin Waugh, J. Andrew (Drew) Bagnell

AAAI Workshop on Computer Poker and Imperfect Information, March, 2015

An Invitation to Imitation
J. Andrew (Drew) Bagnell

CMU-RI-TR-15-08, Robotics Institute, Carnegie Mellon University, March, 2015

CHIMP, the CMU Highly Intelligent Mobile Platform
Anthony (Tony) Stentz, Herman Herman, Alonzo Kelly, Eric Meyhofer, Galen Clark Haynes, David Stager, Brian Zajac, J. Andrew (Drew) Bagnell, Jordan Brindza, Christopher Dellin, Michael George, Jose Gonzalez-Mora, Sean Hyde, Morgan Jones, Michel Laverne, Maxim Likhachev, Levi Lister, Matthew D. Powers, Oscar Ramos, Justin Ray, David P. Rice, Justin Scheifflee, Raumi Sidki, Siddhartha Srinivasa, Kyle Strabala, Jean Philippe Tardif, Jean-Sebastien Valois, J Michael Vandeweghe, Michael D. Wagner and Carl Wellington

Journal of Field Robotics (JFR), Special Issue: Special issue on DARPA Robotics Challenge (DRC), Vol. 32, No. 2, pp. 209-228, March, 2015

A Unified View of Large-scale Zero-sum Equilibrium Computation
Kevin Waugh and J. Andrew (Drew) Bagnell

AAAI Workshop on Computer Poker and Imperfect Information, January, 2015

Approximate MaxEnt Inverse Optimal Control and its Application for Mental Simulation of Human Interactions
De-An Huang, Amir-massoud Farahmand, Kris M. Kitani and J. Andrew (Drew) Bagnell

AAAI Conference on Artificial Intelligence, January, 2015

Improving Multi-step Prediction of Learned Time Series Models
Arun Venkatraman, Martial Hebert and J. Andrew (Drew) Bagnell

Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), January, 2015

Learning to Manipulate Unknown Objects in Clutter by Reinforcement
Abdeslam Boularias, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI), January, 2015

Solving Games with Functional Regret Estimation
Kevin Waugh, Dustin Morrill, J. Andrew (Drew) Bagnell and Michael Bowling

AAAI Conference on Artificial Intelligence, January, 2015

Submodular Surrogates for Value of Information
Yuxin Chen, Shervin Javdani, Amin Karbasi, J. Andrew (Drew) Bagnell, Siddhartha Srinivasa and Andreas Krause

The Twenty-Ninth AAAI Conference on Artificial Intelligence (AAAI-15), January, 2015

Efficient Optimization for Autonomous Robotic Manipulation of Natural Objects
Abdeslam Boularias, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Proceedings of the Twenty-Eighth AAAI Conference on Artificial Intelligence (AAAI), pp. 2520-2526, November, 2014

Pose Machines: Articulated Pose Estimation via Inference Machines
Varun Ramakrishna, Daniel Munoz, Martial Hebert, J. Andrew (Drew) Bagnell and Yaser Ajmal Sheikh

CMU-RI-TR-, European Conference on Computer Vision, July, 2014

Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi andreas Krause, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

CMU-RI-TR-14-03, Robotics Institute, Carnegie Mellon University, April, 2014

Near Optimal Bayesian Active Learning for Decision Making
Shervin Javdani, Yuxin Chen, Amin Karbasi andreas Krause, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

Proceedings of the 17th International Conference on Artificial Intelligence and Statistics (AISTATS), April, 2014

Human-Inspired Force Compliant Grasping Primitives
Moslem Kazemi, Jean-Sebastien Valois, J. Andrew (Drew) Bagnell and Nancy Pollard

Autonomous Robots, March, 2014

Reinforcement Learning in Robotics: A Survey
J. Kober, J. Andrew (Drew) Bagnell and J. Peters

International Journal of Robotics Research, July, 2013

Knapsack Constrained Contextual Submodular List Prediction with Application to Multi-document Summarization
Jiaji Zhou, Stephane Ross, Yisong Yue, Debadeepta Dey and J. Andrew (Drew) Bagnell

ICML 2013 Workshop on Inferning: Interactions between Inference and Learning, June, 2013

Learning Policies for Contextual Submodular Prediction
Stephane Ross, Jiaji Zhou, Yisong Yue, Debadeepta Dey and J. Andrew (Drew) Bagnell

The 30th International Conference on Machine Learning (ICML 2013), June, 2013

Perceiving, Learning, and Exploiting Object Affordances for Autonomous Pile Manipulation
Dov Katz, Arun Venkatraman, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Robotics: Science and Systems Conference, June, 2013

CHOMP: Covariant Hamiltonian Optimization for Motion Planning
Matthew Zucker, Nathan Ratliff, Anca Dragan, Mihail Pivtoraiko, Matthew Klingensmith, Christopher Dellin, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

International Journal of Robotics Research, May, 2013

Closed-loop Servoing using Real-time Markerless Arm Tracking
Matthew Klingensmith, Thomas Galluzzo, Christopher Dellin, Moslem Kazemi, J. Andrew (Drew) Bagnell and Nancy Pollard

International Conference on Robotics And Automation (Humanoids Workshop), May, 2013

Efficient 3-D Scene Analysis from Streaming Data
Hanzhang Hu, Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

IEEE International Conference on Robotics and Automation (ICRA), May, 2013

Efficient Temporal Consistency for Streaming Video Scene Analysis
Ondrej Miksik, Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

IEEE International Conference on Robotics and Automation (ICRA), May, 2013

Efficient Touch Based Localization through Submodularity
Shervin Javdani, Matthew Klingensmith, J. Andrew (Drew) Bagnell, Nancy Pollard and Siddhartha Srinivasa

IEEE International Conference on Robotics and Automation (ICRA), May, 2013

Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown 3D Articulated Objects
Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Proceedings of IEEE International Conference on Robotics and Automation, May, 2013

An Architecture for Online Semantic Labeling on UGVs
Arne Suppe, Luis Ernesto Navarro-Serment, Daniel Munoz, Drew Bagnell, Arne Suppe, Luis Ernesto Navarro-Serment, Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

Proc. SPIE 8741, Unmanned Systems Technology XV, April, 2013

Clearing a Pile of Unknown Objects using Interactive Perception
Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Proceedings of IEEE International Conference on Robotics and Automation, March, 2013

Learning Monocular Reactive UAV Control in Cluttered Natural Environments
Stephane Ross, Narek Melik-Barkhudarov, Kumar Shaurya Shankar andreas Wendel, Debadeepta Dey, J. Andrew (Drew) Bagnell and Martial Hebert

IEEE International Conference on Robotics and Automation, March, 2013

The Principle of Maximum Causal Entropy for Estimating Interacting Processes
Brian D. Ziebart, J. Andrew (Drew) Bagnell and Anind Dey

IEEE Transactions on Information Theory, February, 2013

Clearing a Pile of Unknown Objects using Interactive Perception
Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

CMU-RI-TR-12-34, Robotics Institute, Carnegie Mellon University, November, 2012

Learning Monocular Reactive UAV Control in Cluttered Natural Environments
Stephane Ross, Narek Melik-Barkhudarov, Kumar Shaurya Shankar andreas Wendel, Debadeepta Dey, J. Andrew (Drew) Bagnell and Martial Hebert

No. 1211.169, November, 2012

Semi-Autonomous Manipulation of Natural Objects
Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

CMU-RI-TR-12-33, Robotics Institute, Carnegie Mellon University, November, 2012

Activity Forecasting
Kris M. Kitani, Brian D. Ziebart, J. Andrew (Drew) Bagnell and Martial Hebert

European Conference on Computer Vision, October, 2012

An Integrated System for Autonomous Robotics Manipulation
J. Andrew (Drew) Bagnell, Felipe Cavalcanti, Lei Cui, Thomas Galluzzo, Martial Hebert, Moslem Kazemi, Matthew Klingensmith, Jacqueline Libby, Tommy Liu, Nancy Pollard, Mikhail Pivtoraiko, Jean-Sebastien Valois and Ranqi Zhu

IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 2955-2962, October, 2012

Co-inference for Multi-modal Scene Analysis
Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

European Conference on Computer Vision (ECCV), October, 2012

Detecting Interesting Events using Unsupervised Density Ratio Estimation
Yuichi Ito, Kris M. Kitani, J. Andrew (Drew) Bagnell and Martial Hebert

3rd IEEE International Workshop on Analysis and Retrieval of Tracked Events and Motion in Imagery Streams at ECCV2012, October, 2012

Contextual Sequence Optimization with Application to Control Library Optimization
Debadeepta Dey, Tommy Liu, Martial Hebert and J. Andrew (Drew) Bagnell

Robotics Science and Systems, August, 2012

Efficient Touch Based Localization through Submodularity
Shervin Javdani, Matthew Klingensmith, J. Andrew (Drew) Bagnell, Nancy Pollard and Siddhartha Srinivasa

CMU-RI-TR-12-25, Robotics Institute, Carnegie Mellon University, August, 2012

Agnostic System Identification for Model-Based Reinforcement Learning
Stephane Ross and J. Andrew (Drew) Bagnell

Appearing in Proceedings of the 29th International Conference on Machine Learning, July, 2012

Efficient Optimization of Control Libraries
Debadeepta Dey, Tommy Liu, Boris Sofman and J. Andrew (Drew) Bagnell

26th Conference of Association for Advancement of Artificial Intelligence, July, 2012

Robust Object Grasping using Force Compliant Motion Primitives
Moslem Kazemi, Jean-Sebastien Valois, J. Andrew (Drew) Bagnell and Nancy Pollard

Robotics: Science and Systems, July, 2012

Learning Autonomous Driving Styles and Maneuvers from Expert Demonstration
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

International Symposium on Experimental Robotics, June, 2012

Active Learning from Demonstration for Robust Autonomous Navigation
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

IEEE Conference on Robotics and Automation, May, 2012

SpeedBoost: Anytime Prediction with Uniform Near-Optimality
Alexander Grubb and J. Andrew (Drew) Bagnell

Fifteenth International Conference on Artificial Intelligence and Statistics, April, 2012

Interactive Segmentation, Tracking, and Kinematic Modeling of Unknown Articulated Objects
Dov Katz, Moslem Kazemi, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

CMU-RI-TR-12-06, Robotics Institute, Carnegie Mellon University, March, 2012

Predicting Contextual Sequences via Submodular Function Maximization
Debadeepta Dey, Tommy Liu, Martial Hebert and J. Andrew (Drew) Bagnell

CMU-RI-TR-12-05, Robotics Institute, Carnegie Mellon University, February, 2012

Probabilistic Pointing Target Prediction via Inverse Optimal Control
Brian D. Ziebart, Anind Dey and J. Andrew (Drew) Bagnell

CMU-RI-TR-, International Conference on Intelligent User Interfaces (IUI 2012), February, 2012

Reinforcement Planning: RL for Optimal Planners
Matthew Zucker and J. Andrew (Drew) Bagnell

CMU-RI-TR-, IEEE International Conference on Robotics and Automation (ICRA), February, 2012

Robust Object Grasping using Force Compliant Motion Primitives
Moslem Kazemi, Jean-Sebastien Valois, J. Andrew (Drew) Bagnell and Nancy Pollard

CMU-RI-TR-12-04, Robotics Institute, Carnegie Mellon University, January, 2012

Computational Rationalization: The Inverse Equilibrium Problem
Kevin Waugh, Brian D. Ziebart and J. Andrew (Drew) Bagnell

Proceedings of the International Conference on Machine Learning, June, 2011

Efficient Optimization of Control Libraries
Debadeepta Dey, Tommy Liu, Boris Sofman and J. Andrew (Drew) Bagnell

CMU-RI-TR-11-20, Robotics Institute, Carnegie Mellon University, June, 2011

Learning Message-Passing Inference Machines for Structured Prediction
Stephane Ross, Daniel Munoz, Martial Hebert and J. Andrew (Drew) Bagnell

IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June, 2011

3-D Scene Analysis via Sequenced Predictions over Points and Regions
Xuehan Xiong, Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

IEEE International Conference on Robotics and Automation (ICRA), May, 2011

Generalized Boosting Algorithms for Convex Optimization
Alexander Grubb and J. Andrew (Drew) Bagnell

Proceedings of the 28th International Conference on Machine Learning, May, 2011

Maximum Causal Entropy Correlated Equilibria for Markov Games
Brian D. Ziebart, J. Andrew (Drew) Bagnell and Anind Dey

International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011), May, 2011

Segmentation-Based Online Change Detection for Mobile Robots
Bradford Neuman, Boris Sofman, Anthony (Tony) Stentz and J. Andrew (Drew) Bagnell

International Conference on Robotics and Automation, May, 2011

A Reduction of Imitation Learning and Structured Prediction to No-Regret Online Learning
Stephane Ross, Geoffrey Gordon and J. Andrew (Drew) Bagnell

Proceedings of the 14th International Conference on Artifical Intelligence and Statistics (AISTATS), April, 2011

Learning from Demonstration for Autonomous Navigation in Complex Unstructured Terrain
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

International Journal of Robotics Research, Vol. 29, No. 12, pp. 1565 - 1592, October, 2010

Stacked Hierarchical Labeling
Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

European Conference on Computer Vision (ECCV), September, 2010

Space-carving Kernels for Accurate Rough Terrain Estimation
Raia Hadsell, J. Andrew (Drew) Bagnell, Daniel Huber and Martial Hebert

International Journal of Robotics Research, Vol. 29, No. 8, pp. 981-996, July, 2010

Learning for Autonomous Navigation: Advances in Machine Learning for Rough Terrain Mobility
J. Andrew (Drew) Bagnell, David Bradley , David Silver, Boris Sofman and Anthony (Tony) Stentz

IEEE Robotics & Automation Magazine, Vol. 17, No. 2, pp. 74-84, June, 2010

Modeling Interaction via the Principle of Maximum Causal Entropy
Brian D. Ziebart, J. Andrew (Drew) Bagnell and Anind Dey

International Conference on Machine Learning, June, 2010

An Optimization Approach to Rough Terrain Locomotion
Matthew Zucker, J. Andrew (Drew) Bagnell, Chris Atkeson and James Kuffner

IEEE Conference on Robotics and Automation, May, 2010

Anytime Online Novelty Detection for Vehicle Safeguarding
Boris Sofman, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

IEEE International Conference on Robotics and Automation, May, 2010

Boosted Backpropagation Learning for Training Deep Modular Networks
Alexander Grubb and J. Andrew (Drew) Bagnell

Proceedings of the 27th International Conference on Machine Learning, May, 2010

Efficient Reductions for Imitation Learning
Stephane Ross and J. Andrew (Drew) Bagnell

Proceedings of the 13th International Conference on Artificial Intelligence and Statistics (AISTATS), May, 2010

Reinforcement Planning: RL for Optimal Planners
Matthew Zucker and J. Andrew (Drew) Bagnell

CMU-RI-TR-10-14, Robotics Institute, Carnegie Mellon University, April, 2010

Domain Adaptation For Mobile Robot Navigation
David Bradley and J. Andrew (Drew) Bagnell

CMU-RI-TR-, January, 2010

On Two Methods for Semi-Supervised Structured Prediction
Daniel Munoz, J. Andrew (Drew) Bagnell and Martial Hebert

CMU-RI-TR-10-02, Robotics Institute, Carnegie Mellon University, January, 2010

Policy Gradient Methods
Jan Peters and J. Andrew (Drew) Bagnell

Springer Encyclopedia of Machine Learning, January, 2010

Planning-based Prediction for Pedestrians
Brian D. Ziebart, Nathan Ratliff, Garratt Gallagher, Christoph Mertz, Kevin Peterson, J. Andrew (Drew) Bagnell, Martial Hebert , Anind Dey and Siddhartha Srinivasa

Proc. IROS 2009, October, 2009

Perceptual Interpretation for Autonomous Navigation through Dynamic Imitation Learning
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

International Symposium of Robotics Research, August, 2009

Applied Imitation Learning for Autonomous Navigation in Complex Natural Terrain
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Field and Service Robotics, July, 2009

Bandit-Based Online Candidate Selection for Adjustable Autonomy
Boris Sofman, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

7th International Conferences on Field and Service Robotics, July, 2009

Learning to search: Functional gradient techniques for imitation learning
Nathan Ratliff, David Silver and J. Andrew (Drew) Bagnell

Autonomous Robots, Vol. 27, No. 1, pp. 25-53, July, 2009

Accurate Rough Terrain Estimation with Space-Carving Kernels
Raia Hadsell, J. Andrew (Drew) Bagnell, Daniel Huber and Martial Hebert

Proc. Robotics Science and Systems, June, 2009

Contextual Classification with Functional Max-Margin Markov Networks
Daniel Munoz, J. Andrew (Drew) Bagnell, Nicolas Vandapel and Martial Hebert

IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR), June, 2009

Convex Coding
David Bradley and J. Andrew (Drew) Bagnell

Uncertainty in Artificial Intelligence (UAI), June, 2009

CHOMP: Gradient Optimization Techniques for Efficient Motion Planning
Nathan Ratliff, Matthew Zucker, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

IEEE International Conference on Robotics and Automation (ICRA), May, 2009

Convex Coding
David Bradley and J. Andrew (Drew) Bagnell

CMU-RI-TR-09-22, Robotics Institute, Carnegie Mellon University, May, 2009

GATMO: a Generalized Approach to Tracking Movable Objects
Garratt Gallagher, Siddhartha Srinivasa, J. Andrew (Drew) Bagnell and David Ferguson

IEEE International Conference on Robotics and Automation, May, 2009

A Space-Carving Approach to Surface Estimation
Santosh Kumar Divvala, J. Andrew (Drew) Bagnell and Martial Hebert

CMU-RI-TR-, April, 2009

Anytime Online Novelty Detection for Vehicle Safeguarding
Boris Sofman, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

CMU-RI-TR-09-17, Robotics Institute, Carnegie Mellon University, April, 2009

Inverse Optimal Heuristic Control for Imitation Learning
Nathan Ratliff, Brian D. Ziebart, Kevin Peterson, J. Andrew (Drew) Bagnell, Martial Hebert , Anind Dey and Siddhartha Srinivasa

Twelfth International Conference on Artificial Intelligence and Statistics (AIStats), April, 2009

Differentiable Sparse Coding
David Bradley and J. Andrew (Drew) Bagnell

Proceedings of Neural Information Processing Systems 22, December, 2008

Fast Planning for Dynamic Preferences
Brian D. Ziebart, Anind Dey and J. Andrew (Drew) Bagnell

ICAPS: International Conference on Automated Planning and Scheduling, September, 2008

Maximum Entropy Inverse Reinforcement Learning
Brian D. Ziebart andrew Maas, J. Andrew (Drew) Bagnell and Anind Dey

Proceeding of AAAI 2008, July, 2008

Autonomous driving in urban environments: Boss and the Urban Challenge
Christopher Urmson, Joshua Anhalt, Hong Bae, J. Andrew (Drew) Bagnell, Christopher R. Baker, Robert E. Bittner, Thomas Brown, M. N. Clark, Michael Darms, Daniel Demitrish, John M. Dolan, David Duggins, David Ferguson, Tugrul Galatali, Christopher M. Geyer, Michele Gittleman, Sam Harbaugh, Martial Hebert, Thomas Howard, Sascha Kolski, Maxim Likhachev, Bakhtiar Litkouhi, Alonzo Kelly, Matthew McNaughton, Nick Miller, Jim Nickolaou, Kevin Peterson, Brian Pilnick, Raj Rajkumar, Paul Rybski, Varsha Sadekar, Bryan Salesky, Young-Woo Seo, Sanjiv Singh, Jarrod M. Snider, Joshua C. Struble, Anthony (Tony) Stentz, Michael Taylor, William (Red) L. Whittaker, Ziv Wolkowicki, Wende Zhang and Jason Ziglar

Journal of Field Robotics Special Issue on the 2007 DARPA Urban Challenge, Part I, Vol. 25, No. 8, pp. 425-466, June, 2008

High Performance Outdoor Navigation from Overhead Data using Imitation Learning
David Silver, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

Robotics Science and Systems, June, 2008

Adaptive Workspace Biasing for Sampling Based Planners
Matthew Zucker, James Kuffner and J. Andrew (Drew) Bagnell

Proc. IEEE Int'l Conf. on Robotics and Automation, May, 2008

Adaptive workspace biasing for sampling-based planners
Matthew Zucker, James Kuffner and J. Andrew (Drew) Bagnell

CMU-RI-TR-, April, 2008

Human Behavior Modeling with Maximum Entropy Inverse Optimal Control
Brian D. Ziebart andrew L. Maas, J. Andrew (Drew) Bagnell and Anind Dey

CMU-RI-TR-, April, 2008

Navigate Like a Cabbie: Probabilistic Reasoning from Observed Context-Aware Behavior
Brian D. Ziebart andrew Maas, Anind Dey and J. Andrew (Drew) Bagnell

UBICOMP: Ubiquitious Computation, January, 2008

Imitation Learning for Locomotion and Manipulation
Nathan Ratliff, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

CMU-RI-TR-07-45, Robotics Institute, Carnegie Mellon University, December, 2007

Imitation Learning for Locomotion and Manipulation
Nathan Ratliff, J. Andrew (Drew) Bagnell and Siddhartha Srinivasa

IEEE-RAS International Conference on Humanoid Robots, November, 2007

Learning Selectively Conditioned Forest Structures with Applications to DBNs and Classification
Brian D. Ziebart, Anind Dey and J. Andrew (Drew) Bagnell

Proceedings of Uncertainty in Artificial Intelligence (UAI 2007), July, 2007

Tartan Racing: A Multi-Modal Approach to the DARPA Urban Challenge
Christopher Urmson, Joshua Anhalt, J. Andrew (Drew) Bagnell, Christopher R. Baker, Robert E. Bittner, John M. Dolan, David Duggins, David Ferguson , Tugrul Galatali, Hartmut Geyer, Michele Gittleman, Sam Harbaugh, Martial Hebert , Thomas Howard, Alonzo Kelly , David Kohanbash, Maxim Likhachev , Nick Miller, Kevin Peterson, Raj Rajkumar, Paul Rybski, Bryan Salesky, Sebastian Scherer, Young-Woo Seo, Reid Simmons, Sanjiv Singh, Jarrod M. Snider, Anthony (Tony) Stentz , William (Red) L. Whittaker and Jason Ziglar

CMU-RI-TR-, Robotics Institute, Carnegie Mellon University, DARPA Grand Challenge Tech Report, April, 2007

Vegetation Detection for Driving in Complex Environments
David Bradley , Ranjith Unnikrishnan and J. Andrew (Drew) Bagnell

IEEE International Conference on Robotics and Automation, April, 2007

(Online) Subgradient Methods for Structured Prediction
Nathan Ratliff, J. Andrew (Drew) Bagnell and Martin Zinkevich

Eleventh International Conference on Artificial Intelligence and Statistics (AIStats), March, 2007

Boosting Structured Prediction for Imitation Learning
Nathan Ratliff, David Bradley , J. Andrew (Drew) Bagnell and Joel Chestnutt

Advances in Neural Information Processing Systems 19, January, 2007

Creating Low-Cost Soil Maps for Tropical Agriculture using Gaussian Processes
Juan Pablo Gonzalez, Simon Cook, Thomas Oberthur andrew Jarvis, J. Andrew (Drew) Bagnell and M Bernardine Dias

Workshop on AI in ICT for Development (ICTD) at the Twentieth International Joint Conference on Artificial Intelligence (IJCAI 2007), January, 2007

Kernel Conjugate Gradient for Fast Kernel Machines
Nathan Ratliff and J. Andrew (Drew) Bagnell

International Joint Conference on Artificial Intelligence, Vol. 20, January, 2007

Improving Robot Navigation Through Self-Supervised Online Learning
Boris Sofman, Ellie Lin Ratliff, J. Andrew (Drew) Bagnell, John Cole, Nicolas Vandapel and Anthony (Tony) Stentz

Journal of Field Robotics, Vol. 23, No. 12, December, 2006

Experimental Analysis of Overhead Data Processing To Support Long Range Navigation
David Silver, Boris Sofman, Nicolas Vandapel, J. Andrew (Drew) Bagnell and Anthony (Tony) Stentz

IEEE International Conference on Intelligent Robots and Systems (IROS), pp. 2443 - 2450, October, 2006

Improving Robot Navigation Through Self-Supervised Online Learning
Boris Sofman, Ellie Lin Ratliff, J. Andrew (Drew) Bagnell, Nicolas Vandapel and Anthony (Tony) Stentz

Proceedings of Robotics: Science and Systems, August, 2006

Maximum Margin Planning
Nathan Ratliff, J. Andrew (Drew) Bagnell and Martin Zinkevich

International Conference on Machine Learning, July, 2006

On Local Rewards and Scaling Distributed Reinforcement Learning
J. Andrew (Drew) Bagnell and Andrew Ng

Neural Information Processing Systems, May, 2006

Subgradient Methods for Maximum Margin Structured Learning
Nathan Ratliff, J. Andrew (Drew) Bagnell and Martin Zinkevich

CMU-RI-TR-, April, 2006

Terrain Classification from Aerial Data to Support Ground Vehicle Navigation
Boris Sofman, J. Andrew (Drew) Bagnell, Anthony (Tony) Stentz and Nicolas Vandapel

CMU-RI-TR-05-39, Robotics Institute, Carnegie Mellon University, January, 2006

Gaussian Processes for Statistical Soil Modeling of the Tropics
Juan Pablo Gonzalez, J. Andrew (Drew) Bagnell, Simon Cook, Thomas Oberthur andrew Jarvis and Mauricio Rincon

CMU-RI-TR-05-52, Robotics Institute, Carnegie Mellon University, October, 2005

Cost-Sensitive Learning for Confidential Access Control
Young-Woo Seo, J. Andrew (Drew) Bagnell and Katia Sycara

CMU-RI-TR-05-31, Robotics Institute, Carnegie Mellon University, June, 2005

Kernel Conjugate Gradient
Nathan Ratliff and J. Andrew (Drew) Bagnell

CMU-RI-TR-05-30, Robotics Institute, Carnegie Mellon University, June, 2005

Robust Supervised Learning
J. Andrew (Drew) Bagnell

Proceedings of AAAI, June, 2005

Learning Opportunity Costs in Multi-Robot Market Based Planners
Jeff Schneider , David Apfelbaum, J. Andrew (Drew) Bagnell and Reid Simmons

CMU-RI-TR-, April, 2005

Learning Decisions: Robustness, Uncertainty, and Approximation
J. Andrew (Drew) Bagnell

CMU-RI-TR-04-67, Robotics Institute, Carnegie Mellon University, August, 2004

Policy Search by Dynamic Programming
J. Andrew (Drew) Bagnell, Sham Kakade andrew Ng and Jeff Schneider

Neural Information Processing Systems, Vol. 16, December, 2003

Policy Search in Reproducing Kernel Hilbert Space
J. Andrew (Drew) Bagnell and Jeff Schneider

CMU-RI-TR-03-45, Robotics Institute, Carnegie Mellon University, November, 2003

Covariant Policy Search
J. Andrew (Drew) Bagnell and Jeff Schneider

Proceeding of the International Joint Conference on Artifical Intelligence, August, 2003

Learning with scope; with application to information extraction and classification
David Blei, J. Andrew (Drew) Bagnell and Andrew McCallum

Uncertainty in Artificial Intelligence, pp. 53-60, June, 2002

Learning with Scope, with Application to Information Extraction and Classification
David Blei, J. Andrew (Drew) Bagnell and Andrew Mccallum

CMU-RI-TR-, April, 2002

Solving Uncertain Markov Decision Problems
J. Andrew (Drew) Bagnell, Andrew Y. Ng and Jeff Schneider

CMU-RI-TR-01-25, Robotics Institute, Carnegie Mellon University, August, 2001

Autonomous Helicopter Control using Reinforcement Learning Policy Search Methods
J. Andrew (Drew) Bagnell and Jeff Schneider

Proceedings of the International Conference on Robotics and Automation 2001, May, 2001

Stabilizing Human Control Strategies through Reinforcement Learning
Michael Nechyba and J. Andrew (Drew) Bagnell

Proc. IEEE Hong Kong Symp. on Robotics and Control, Vol. 1, pp. 39-44, April, 1999

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