2017


J.P. Hanna, P. Stone, and S. Niekum. Bootstrapping with Models: Confidence Intervals for Off-Policy Evaluation. Proceedings of the 16th International Conference on Autonomous Agents and Multiagent Systems (AAMAS), May 2017.


2016


P. Khandelwal, E. Liebman, S. Niekum, and P. Stone. On the Analysis of Complex Backup Strategies in Monte Carlo Tree Search. International Conference on Machine Learning (ICML), June 2016.


2015


P.S. Thomas, S. Niekum, G. Theocharous, and G.D. Konidaris. Policy Evaluation Using the Omega-Return. Advances in Neural Information Processing Systems 29 (NIPS), pages 334–342, December 2015.

S. Niekum, S. Osentoski, C.G. Atkeson, and A.G. Barto. Online Bayesian Changepoint Detection for Articulated Motion Models. IEEE International Conference on Robotics and Automation (ICRA), May 2015. [Code] [bibtex]

K. Hausman, S. Niekum, S. Osentoski, and G. Sukhatme. Active Articulation Model Estimation through Interactive Perception. IEEE International Conference on Robotics and Automation (ICRA), May 2015. [Code] [bibtex]

S. Niekum, S. Osentoski, G.D. Konidaris, S. Chitta, B. Marthi, and A.G. Barto. Learning Grounded Finite-State Representations from Unstructured Demonstrations. International Journal of Robotics Research (IJRR), Vol. 34(2), pages 131-157, February 2015. [Video] [Code] [bibtex] [Freely accessible draft]

S. Niekum. A Brief Introduction to Bayesian Nonparametric Methods for Clustering and Time Series Analysis. Technical report CMU-RI-TR-15-02, Robotics Institute, Carnegie Mellon University, January 2015. [bibtex]


2014


S. Niekum, S. Osentoski, C.G. Atkeson, and A.G. Barto. Learning Articulation Changepoint Models from Demonstration. R:SS Workshop on Learning Plans with Context from Human Signals, July 2014. [Code]

S. Niekum, S. Osentoski, C.G. Atkeson, and A.G. Barto. CHAMP: Changepoint Detection Using Approximate Model Parameters. Technical report CMU-RI-TR-14-10, Robotics Institute, Carnegie Mellon University, June 2014. [Code] [bibtex]


2013


S. Niekum. Semantically Grounded Learning from Unstructured Demonstrations. Doctoral Dissertation, Department of Computer Science, University of Massachusetts Amherst, September 2013.

S. Niekum, S. Osentoski, S. Chitta, B. Marthi, and Andrew G. Barto. Incremental Semantically Grounded Learning from Demonstration. Robotics: Science and Systems 9 (RSS), June 2013. [Video] [bibtex]

G.D. Konidaris, S. Kuindersma, S. Niekum, R.A. Grupen and A.G. Barto. Robot Learning: Some Recent Examples. In Proceedings of the Sixteenth Yale Workshop on Adaptive and Learning Systems, pages 71-76, June 2013.

S. Niekum. An Integrated System for Learning Multi-Step Robotic Tasks from Unstructured Demonstrations. AAAI Spring Symposium: Reintegrating AI II, March 2013.


2012


S. Niekum, S. Osentoski, G.D. Konidaris, and Andrew G. Barto. Learning and Generalization of Complex Tasks from Unstructured Demonstrations. IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pages 5239-5246, October 2012. [Video] [Code] [bibtex]

S. Niekum. Complex Task Learning from Unstructured Demonstrations. AAAI Doctoral Consortium, July 2012.


2011


G.D. Konidaris, S. Niekum, and P.S. Thomas. TD γ: Reevaluating Complex Backups in Temporal Difference Learning. Advances in Neural Information Processing Systems 24 (NIPS), pages 2402-2410, December 2011. [bibtex]

S. Niekum and A.G. Barto. Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. Advances in Neural Information Processing Systems 24 (NIPS), pages 1818-1826, December 2011. [bibtex]

S. Niekum and A.G. Barto. Clustering via Dirichlet Process Mixture Models for Portable Skill Discovery. AAAI Workshop on Lifelong Learning from Sensorimotor Experience, August 2011.


2010


S. Niekum, A.G. Barto, and L. Spector. Genetic Programming for Reward Function Search. IEEE Transactions on Autonomous Mental Development, vol.2, no.2, pages 83-90, June 2010. [Code] [bibtex]

S. Niekum. Evolved Intrinsic Reward Functions for Reinforcement Learning. Proceedings of the Twenty-Fourth Conference on Artificial Intelligence (AAAI), July 2010. (Extended abstract)


2005


S. Niekum. Reliable Rock Detection and Classification for Autonomous Science. Carnegie Mellon Senior Thesis, April 2005.

D.R. Thompson, S. Niekum, T. Smith, and D. Wettergreen. Automatic Detection and Classification of Geological Features of Interest. IEEE Aerospace Conference Proceedings, March 2005. [bibtex]

T. Smith, S. Niekum, D.R. Thompson, and D. Wettergreen. Concepts for Science Autonomy During Robotic Traverse and Survey. IEEE Aerospace Conference Proceedings, March 2005. [bibtex]