Brian Ziebart -- Purposeful Adaptive Behavior Prediction (original) (raw)

Probabilistic Pointing Target Prediction via Inverse Optimal Control
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell
International Conference on Intelligent User Interfaces (IUI 2012)
[abstract] [pdf] [bibtex]
Best Paper Award Nominee

Factorized Decision Forecasting via Combining Value-based and Reward-based Estimation
Brian D. Ziebart
Allerton Conference on Communication, Control and Computing (Allerton 2011)
[abstract] [pdf] [bibtex]

Process-Conditioned Investing with Incomplete Information using Maximum Causal Entropy
Brian D. Ziebart
International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering (MaxEnt 2011)
[abstract] [pdf] [bibtex]

Computational Rationalization: The Inverse Equilibrium Problem
Kevin Waugh, Brian D. Ziebart, and J. Andrew Bagnell
International Conference on Machine Learning (ICML 2011).
[abstract] [pdf] [bibtex]
Best Paper Award
(An earlier version appeared in Workshop on Decision Making with Multiple Imperfect Decision Makers at NIPS 2010.)

Maximum Causal Entropy Correlated Equilibria for Markov Games
Brian D. Ziebart, J. Andrew Bagnell, and Anind K. Dey
International Conference on Autonomous Agents and Multiagent Systems (AAMAS 2011).
[abstract] [pdf] [bibtex]
(An earlier version appeared in the Interactive Decision Theory and Game Theory Workshop at AAAI 2010.)

Learning Patterns of Pick-ups and Drop-offs to Support Busy Family Coordination
Scott Davidoff, Brian D. Ziebart, John Zimmerman, and Anind K. Dey
SIG CHI Conference on Human Factors in Computing Systems (CHI 2011).
[abstract] [pdf] [bibtex]

Modeling Purposeful Adaptive Behavior with the Principle of Maximum Causal Entropy
Brian D. Ziebart
PhD Thesis. Department of Machine Learning. December 2010.
[abstract] [pdf] [bibtex]
School of Computer Science Distinguished Dissertation Award, Honorable Mention

Modeling Interaction via the Principle of Maximum Causal Entropy
Brian D. Ziebart, J. Andrew Bagnell, and Anind K. Dey
International Conference on Machine Learning (ICML 2010).
[abstract] [pdf] [bibtex]
Best Student Paper Award, Runner-Up
(An earlier version appeared in Workshop on Probabilistic Approaches for Robotics and Control at NIPS 2009.)

Planning-based Prediction for Pedestrians
Brian D. Ziebart, Nathan Ratliff, Garratt Gallagher, Christoph Mertz, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, A K. Dey, Siddhartha Srinivasa
International Conference on Intelligent Robots and Systems (IROS 2009).
[abstract] [pdf] [bibtex]

Inverse Optimal Heuristic Control for Imitation Learning
Nathan Ratliff, Brian D. Ziebart, Kevin Peterson, J. Andrew Bagnell, Martial Hebert, Anind K. Dey, Siddhartha Srinivasa
Artificial Intelligence and Statistics (AISTATS 2009).
[abstract] [pdf] [bibtex]

Human Behavior Modeling with Maximum Entropy Inverse Optimal Control
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, Anind K. Dey
AAAI Spring Symposium on Human Behavior Modeling. 2009.
[pdf]

Navigate Like a Cabbie: Probabilistic Reasoning from Observed Context-Aware Behavior
Brian D. Ziebart, Andrew Maas, Anind K. Dey, and J. Andrew Bagnell.
International Conference on Ubiquitous Computing (Ubicomp 2008).
[abstract] [pdf] [bibtex]

Fast Planning for Dynamic Preferences
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell.
International Conference on Automated Planning and Scheduling (ICAPS 2008).
[abstract] [pdf] [bibtex]

Maximum Entropy Inverse Reinforcement Learning
Brian D. Ziebart, Andrew Maas, J. Andrew Bagnell, and Anind K. Dey.
AAAI Conference on Artificial Intelligence (AAAI 2008).
[abstract] [pdf] [bibtex]
(An earlier version appeared in Workshop on Robotic Challenges for Machine Learning at NIPS 2007.)

Learning Selectively Conditioned Forest Structures with Applications to DBNs and Classification
Brian D. Ziebart, Anind K. Dey, and J. Andrew Bagnell.
Uncertainty in Artificial Intelligence (UAI 2007).
[abstract] [pdf] [bibtex]

Learning Automation Policies for Pervasive Computing Environments
Brian D. Ziebart, Dan Roth, Roy H. Campbell, and Anind K. Dey.
IEEE International Conference on Autonomic Computing (ICAC 2005).
[abstract] [pdf] [bibtex]

Towards a Pervasive Computing Benchmark
Anand Ranganathan, Jalal Al-Muhtadi, Jacob Biehl, Brian Ziebart, Roy H. Campbell, and Brian Bailey.
PerWare '05 Workshop on Support for Pervasive Computing at PerCom 2005.
[pdf]

System Support for Rapid Ubiquitous Computing Application Development and Evaluation
Manuel Roman, Jalal Al-Muhtadi, Brian Ziebart, and Roy H. Campbell.
Systems Support for Ubiquitous Computing Workshop, at_UbiComp 2003._
[pdf]

Dynamic Application Composition: Customizing the Behavior of an Active Space
Manuel Roman, Brian Ziebart, and Roy H. Campbell.
IEEE International Conference on Pervasive Computing and Communications (PerCom 2003).
[pdf]