Jacob W. Crandall

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Michael A. GoodrichComputer Science Department, Brigham Young UniversityVerified email at cs.byu.edu
M. CummingsProfessor, Duke UniversityVerified email at duke.edu
Iyad RahwanCenter for Humans & Machines, Max Planck Institute for Human DevelopmentVerified email at mpib-berlin.mpg.de
Jean-François BonnefonToulouse School of Economics - TSMR - IAST - CNRS - ANITIVerified email at tse-fr.eu
Carl NehmeVerified email at mit.edu
Mayada OudahNew York University Abu DhabiVerified email at nyu.edu
Manuel CebrianMax Planck Research Group Leader, Max Planck Institute for Human DevelopmentVerified email at mpib-berlin.mpg.de
Azim ShariffAssociate Professor; University of British ColumbiaVerified email at psych.ubc.ca
Subramanian RamamoorthyProfessor of Robot Learning and Autonomy, School of Informatics, University of EdinburghVerified email at ed.ac.uk
Stefano V. AlbrechtSchool of Informatics, University of EdinburghVerified email at five.ai
Thomas J. PalmerPhD Candidate, School of Computer Science, University of OklahomaVerified email at ou.edu
Sherief AbdallahUniversity of Edinburgh and British University in DubaiVerified email at ieee.org
Wen ShenTulane UniversityVerified email at uci.edu
Tim McLainProfessor of Mechanical Engineering, Brigham Young UniversityVerified email at byu.edu
Cristina Videira LopesInformation and Computer Sciences, University of California, IrvineVerified email at ics.uci.edu
Emilia Barakovaassistant professor, Eindhoven University of TechnologyVerified email at tue.nl
Maria GiniProfessor of Computer Science and Engineering, University of MinnesotaVerified email at umn.edu
Nicholas Johnson3M, University of MinnesotaVerified email at cs.umn.edu
Zaid AlmahmoudResearch Associate of Computer Science, Khalifa University of Science & TechnologyVerified email at kustar.ac.ae
Morgan QuigleyOpen Source Robotics FoundationVerified email at osrfoundation.org

Jacob W. Crandall

Professor of Computer Science, Brigham Young University

Verified email at cs.byu.edu - Homepage

Artificial intelligence human-machine interaction multi-agent systems machine learning game theory


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Machine behaviour I Rahwan, M Cebrian, N Obradovich, J Bongard, JF Bonnefon, C Breazeal, ... Nature 568 (7753), 477-486, 2019	362	2019
Validating human-robot interaction schemes in multitasking environments JW Crandall, MA Goodrich, DR Olsen, CW Nielsen IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2005	314	2005
Experiments in adjustable autonomy MA Goodrich, DR Olsen, JW Crandall, TJ Palmer Proceedings of IJCAI Workshop on autonomy, delegation and control …, 2001	284	2001
Characterizing efficiency of human robot interaction: A case study of shared-control teleoperation JW Crandall, MA Goodrich IEEE/RSJ international conference on intelligent robots and systems 2, 1290-1295, 2002	174	2002
Managing autonomy in robot teams: observations from four experiments MA Goodrich, TW McLain, JD Anderson, J Sun, JW Crandall 2007 2nd ACM/IEEE International Conference on Human-Robot Interaction (HRI …, 2007	136	2007
Cooperating with machines JW Crandall, M Oudah, F Ishowo-Oloko, S Abdallah, JF Bonnefon, ... Nature communications 9 (1), 1-12, 2018	114	2018
Developing performance metrics for the supervisory control of multiple robots JW Crandall, ML Cummings Proceedings of the ACM/IEEE international conference on Human-robot …, 2007	108	2007
Predicting operator capacity for supervisory control of multiple UAVs ML Cummings, CE Nehme, J Crandall, P Mitchell Innovations in Intelligent Machines-1, 11-37, 2007	91	2007
Identifying predictive metrics for supervisory control of multiple robots JW Crandall, ML Cummings IEEE Transactions on Robotics 23 (5), 942-951, 2007	82	2007
Experiments in adjustable autonomy JW Crandall, MA Goodrich 2001 IEEE International Conference on Systems, Man and Cybernetics. e …, 2001	79	2001
Teleoperation and beyond for assistive humanoid robots MA Goodrich, JW Crandall, E Barakova Reviews of Human factors and ergonomics 9 (1), 175-226, 2013	58	2013
Learning to compete, coordinate, and cooperate in repeated games using reinforcement learning JW Crandall, MA Goodrich Machine Learning 82 (3), 281-314, 2011	57	2011
An operator function taxonomy for unmanned aerial vehicle missions CE Nehme, JW Crandall, ML Cummings 12th international command and control research and technology symposium, 19-21, 2007	55*	2007
Learning to compete, compromise, and cooperate in repeated general-sum games JW Crandall, MA Goodrich Proceedings of the 22nd international conference on machine learning, 161-168, 2005	54	2005
Belief and truth in hypothesised behaviours SV Albrecht, JW Crandall, S Ramamoorthy Artificial Intelligence 235, 63-94, 2016	53	2016
Computing the effects of operator attention allocation in human control of multiple robots JW Crandall, ML Cummings, M Della Penna, PMA De Jong IEEE Transactions on Systems, Man, and Cybernetics-Part A: Systems and …, 2010	52	2010
Towards predicting robot team performance JW Crandall, CW Nielsen, MA Goodrich SMC'03 Conference Proceedings. 2003 IEEE International Conference on Systems …, 2003	50	2003
Neglect tolerant teaming: Issues and dilemmas MA Goodrich, JW Crandall, JL Stimpson Proceedings of the 2003 AAAI Spring Symposium on Human Interaction with …, 2003	41	2003
Identifying generalizable metric classes to evaluate human-robot teams P Pina, M Cummings, J Crandall, M Della Penna Proc. 3rd Ann. Conf. Human-Robot Interaction, 13-20, 2008	39	2008
Behavioural evidence for a transparency–efficiency tradeoff in human–machine cooperation F Ishowo-Oloko, JF Bonnefon, Z Soroye, J Crandall, I Rahwan, T Rahwan Nature Machine Intelligence 1 (11), 517-521, 2019	38	2019

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