Scott Niekum

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Daniel S. BrownAssistant Professor, Robotics Center and School of Computing, University of UtahVerified email at cs.utah.edu
Andrew BartoUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Peter StoneProfessor of Computer Science, The University of Texas at AustinVerified email at cs.utexas.edu
Wonjoon GooUniversity of Texas at AustinVerified email at cs.utexas.edu
Sarah OsentoskiIron OxVerified email at ironox.com
George KonidarisBrownVerified email at cs.brown.edu
Yuchen CuiPostdoc at StanfordVerified email at stanford.edu
Akanksha SaranMicrosoft ResearchVerified email at microsoft.com
Andrea ThomazInteractive Computing, Georgia Institute of TechnologyVerified email at ece.utexas.edu
Ufuk TopcuThe University of Texas at AustinVerified email at utexas.edu
Philip ThomasUniversity of Massachusetts AmherstVerified email at cs.umass.edu
Josiah P. HannaAssistant Professor, University of Wisconsin--MadisonVerified email at cs.wisc.edu
Elaine Schaertl ShortComputer Science, Tufts UniversityVerified email at tufts.edu
Raymond MooneyProfessor of Computer Science, University of Texas at AustinVerified email at cs.utexas.edu
Mohammed AlshiekhResearcher at University of Texas at AustinVerified email at utexas.edu
Ajinkya JainRoboticist, Intrinsic.ai (An Alphabet Company)Verified email at google.com
Prasoon GoyalApplied Scientist, AmazonVerified email at cs.utexas.edu
Bhaskara MarthiVerified email at csail.mit.edu
Sachin ChittaDirector of Robotics Research, AutodeskVerified email at autodesk.com
Alessandro AllieviImperial College LondonVerified email at imperial.ac.uk

Scott Niekum

Associate Professor, University of Massachusetts Amherst

Verified email at cs.umass.edu - Homepage

Imitation Learning Reinforcement Learning AI Safety Robotics


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Safe reinforcement learning via shielding M Alshiekh, R Bloem, R Ehlers, B Könighofer, S Niekum, U Topcu Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	511	2018
A review of robot learning for manipulation: Challenges, representations, and algorithms O Kroemer, S Niekum, G Konidaris The Journal of Machine Learning Research 22 (1), 1395-1476, 2021	254	2021
Extrapolating Beyond Suboptimal Demonstrations via Inverse Reinforcement Learning from Observations D Brown, W Goo, P Nagarajan, S Niekum International Conference on Machine Learning, 2019	234	2019
Learning grounded finite-state representations from unstructured demonstrations S Niekum, S Osentoski, G Konidaris, S Chitta, B Marthi, AG Barto The International Journal of Robotics Research 34 (2), 131-157, 2015	227	2015
Learning and Generalization of Complex Tasks from Unstructured Demonstrations S Niekum, S Osentoski, G Konidaris, AG Barto IEEE/RSJ International Conference on Intelligent Robots and Systems, 5239-5246, 2012	225	2012
Incremental Semantically Grounded Learning from Demonstration S Niekum, S Chitta, B Marthi, S Osentoski, AG Barto Robotics: Science and Systems 2013, 2013	141	2013
Better-than-Demonstrator Imitation Learning via Automatically-Ranked Demonstrations D Brown, W Goo, S Niekum Conference on Robot Learning, 2019	122	2019
Using Natural Language for Reward Shaping in Reinforcement Learning P Goyal, S Niekum, R Mooney International Joint Conference on Artificial Intelligence, 2019	100	2019
Safe imitation learning via fast bayesian reward inference from preferences D Brown, R Coleman, R Srinivasan, S Niekum International Conference on Machine Learning, 1165-1177, 2020	96*	2020
Active articulation model estimation through interactive perception K Hausman, S Niekum, S Osentoski, GS Sukhatme 2015 IEEE International Conference on Robotics and Automation (ICRA), 3305-3312, 2015	86	2015
Machine Teaching for Inverse Reinforcement Learning: Algorithms and Applications D Brown, S Niekum AAAI Conference on Artificial Intelligence, 2019	75	2019
Active reward learning from critiques Y Cui, S Niekum 2018 IEEE international conference on robotics and automation (ICRA), 6907-6914, 2018	75	2018
Genetic programming for reward function search S Niekum, AG Barto, L Spector IEEE Transactions on Autonomous Mental Development 2 (2), 83-90, 2010	70*	2010
Automatic detection and classification of geological features of interest DR Thompson, S Niekum, T Smith, D Wettergreen Proceedings of the IEEE Aerospace Conference, 2005	70*	2005
Bootstrapping with models: Confidence intervals for off-policy evaluation J Hanna, P Stone, S Niekum Proceedings of the AAAI Conference on Artificial Intelligence 31 (1), 2017	67	2017
Importance Sampling Policy Evaluation with an Estimated Behavior Policy J Hanna, S Niekum, P Stone International Conference on Machine Learning, 2019	56	2019
Risk-Aware Active Inverse Reinforcement Learning D Brown, Y Cui, S Niekum Conference on Robot Learning, 2018	55	2018
Online bayesian changepoint detection for articulated motion models S Niekum, S Osentoski, CG Atkeson, AG Barto 2015 IEEE international conference on robotics and automation (ICRA), 1468-1475, 2015	48	2015
Screwnet: Category-independent articulation model estimation from depth images using screw theory A Jain, R Lioutikov, C Chuck, S Niekum 2021 IEEE International Conference on Robotics and Automation (ICRA), 13670 …, 2021	47	2021
Efficient probabilistic performance bounds for inverse reinforcement learning D Brown, S Niekum Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018	43	2018

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