Lucian Busoniu received the M.Sc. degree (valedictorian) from the Technical University of Cluj-Napoca, Romania, in 2003 and the Ph.D. degree (cum laude) from the Delft University of Technology, the Netherlands, in 2009. He has held research positions in the Netherlands and France, and is currently an associate professor with the Department of Automation at the Technical University of Cluj-Napoca. His fundamental interests include planning-based methods for nonlinear optimal control, reinforcement learning and dynamic programming with function approximation, and multiagent systems; while his practical focus is applying these techniques to robotics. He has coauthored a book and more than 50 papers and book chapters on these topics. He was the recipient of the 2009 Andrew P. Sage Award for the best paper in the IEEE Transactions on Systems, Man, and Cybernetics.
Levente Tamas received the M.Sc. (valedictorian) and the Ph.D. degree in electrical engineering from Technical University of Cluj-Napoca, Romania, in 2005 and 2010, respectively. He took part in several postdoctoral programs dealing with 3D perception and robotics, the most recent one spent at the Bern University of Applied Sciences, Switzerland. He is currently with the Department of Automation, Technical University of Cluj-Napoca, Romania. His research focuses on 3D perception and planning for autonomous mobile robots, and has resulted in several well ranked conference papers, journal articles, and book chapters in this field.
3 Ebooks bởi Lucian Busoniu
Lucian Bușoniu & Levente Tamás: Handling Uncertainty and Networked Structure in Robot Control
This book focuses on two challenges posed in robot control by the increasing adoption of robots in the everyday human environment: uncertainty and networked communication. Part I of the book describe …
PDF
Anh
€96.29
Robert Babuska & Lucian Busoniu: Reinforcement Learning and Dynamic Programming Using Function Approximators
From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has p …
EPUB
Anh
DRM
€64.34
Robert Babuska & Lucian Busoniu: Reinforcement Learning and Dynamic Programming Using Function Approximators
From household appliances to applications in robotics, engineered systems involving complex dynamics can only be as effective as the algorithms that control them. While Dynamic Programming (DP) has p …
PDF
Anh
DRM
€64.18