Biblio

Found 9 results

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C

Dong, S., P. Conrad, J. A. Shah, B. Williams, D. Mittman, M. Ingham, and V. Verma, "Compliant Task Execution and Learning for Safe Mixed-Initiative Human-Robot Operations", AIAA Infotech@Aerospace (I@A), 06/2011.

D

Gombolay, M. C., R. A. Gutierrez, S. G. Clarke, G. F. Sturla, and J. A. Shah, "Decision-Making Authority, Team Efficiency and Human Worker Satisfaction in Mixed Human-Robot Teams", Autonomous Robots, vol. 39, issue 3, pp. 312, 10/2015.

F

Shah, J. A., P. Conrad, and B. Williams, "Fast Distributed Multi-agent Plan Execution with Dynamic Task Assignment and Scheduling", International Conference on Automated Planning and Scheduling (ICAPS) [34% acceptance rate], 09/2009.

Shah, J. A., P. Conrad, and B. Williams, "Flexible Execution of Plans with Choice", International Conference on Automated Planning and Scheduling (ICAPS), 09/2009.

H

Booth, S., S. Sharma, S. Chung, J. Shah, and E. L. Glassman, "How to Understand Your Robot: A Design Space Informed by Human Concept Learning", International Conference on Robotics and Automation (ICRA), Workshop on Social Intelligence in Humans and Robots (SIHR), 05/2021.

Nikolaidis, S., P. A. Lasota, Gregory Rossano, Carlos Martinez, Thomas Fuhlbrigge, and J. Shah, "Human-Robot Collaboration in Manufacturing: Quantitative Evaluation of Predictable, Convergent Joint Action", International Symposium on Robotics (ISR) [Best Paper Nomination], 10/2013.

I

Kim, B., C. M. Chacha, and J. A. Shah, "Inferring Robot Task Plans from Human Team Meetings: A Generative Modeling Approach with Logic-Based Prior", AAAI Conference on Artificial Intelligence (AAAI) [29% Acceptance Rate], 07/2013.

Kim, B., C. M. Chacha, and J. A. Shah, "Inferring Team Task Plans from Human Meetings: A Generative Modeling Approach with Logic-Based Prior", Journal of Artificial Intelligence Research (JAIR) , pp. 361-398, 2015.

R

Booth, S., S. Sharma, S. Chung, J. Shah, and E. L. Glassman, "Revisiting Human-Robot Teaching and Learning Through the Lens of Human Concept Learning Theory", ACM/IEEE International Conference on Human-Robot Interaction (HRI), 03/2022.