Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Filters

Rushikesh Kamalapurkar

Showing results (1-10 of 7) with videos related to

Pageof 1
Sort By:
IEEE Transactions on Neural Networks and Learning Systems|October 30, 2018
The State Following Approximation MethodJoel A Rosenfeld, Rushikesh Kamalapurkar, Warren E Dixon
Frontiers in Robotics and AI|July 18, 2022
Editorial: Safety in Collaborative Robotics and Autonomous SystemsAshwin Dani, Zhen Kan, Rushikesh Kamalapurkar, et al.
IEEE Transactions on Neural Networks and Learning Systems|February 11, 2016
Model-Based Reinforcement Learning for Infinite-Horizon Approximate Optimal TrackingRushikesh Kamalapurkar, Lindsey Andrews, Patrick Walters, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 15, 2014
Approximate N-Player Nonzero-Sum Game Solution for an Uncertain Continuous Nonlinear SystemMarcus Johnson, Rushikesh Kamalapurkar, Shubhendu Bhasin, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 18, 2018
Approximate Dynamic Programming: Combining Regional and Local State Following ApproximationsPatryk Deptula, Joel A Rosenfeld, Rushikesh Kamalapurkar, et al.
Frontiers in Robotics and AI|January 3, 2022
Safe Model-Based Reinforcement Learning for Systems With Parametric UncertaintiesS M Nahid Mahmud, Scott A Nivison, Zachary I Bell, et al.
IEEE Transactions on Cybernetics|August 5, 2015
Identification-Based Closed-Loop NMES Limb Tracking With Amplitude-Modulated Control InputTeng-Hu Cheng, Qiang Wang, Rushikesh Kamalapurkar, et al.
Pageof 1

Showing results (1-10 of 7) with videos related to

Sort By:
Pageof 1
IEEE Transactions on Neural Networks and Learning Systems|October 30, 2018
The State Following Approximation MethodJoel A Rosenfeld, Rushikesh Kamalapurkar, Warren E Dixon
Frontiers in Robotics and AI|July 18, 2022
Editorial: Safety in Collaborative Robotics and Autonomous SystemsAshwin Dani, Zhen Kan, Rushikesh Kamalapurkar, et al.
IEEE Transactions on Neural Networks and Learning Systems|February 11, 2016
Model-Based Reinforcement Learning for Infinite-Horizon Approximate Optimal TrackingRushikesh Kamalapurkar, Lindsey Andrews, Patrick Walters, et al.
IEEE Transactions on Neural Networks and Learning Systems|October 15, 2014
Approximate N-Player Nonzero-Sum Game Solution for an Uncertain Continuous Nonlinear SystemMarcus Johnson, Rushikesh Kamalapurkar, Shubhendu Bhasin, et al.
IEEE Transactions on Neural Networks and Learning Systems|May 18, 2018
Approximate Dynamic Programming: Combining Regional and Local State Following ApproximationsPatryk Deptula, Joel A Rosenfeld, Rushikesh Kamalapurkar, et al.
Frontiers in Robotics and AI|January 3, 2022
Safe Model-Based Reinforcement Learning for Systems With Parametric UncertaintiesS M Nahid Mahmud, Scott A Nivison, Zachary I Bell, et al.
IEEE Transactions on Cybernetics|August 5, 2015
Identification-Based Closed-Loop NMES Limb Tracking With Amplitude-Modulated Control InputTeng-Hu Cheng, Qiang Wang, Rushikesh Kamalapurkar, et al.
Pageof 1