Background
Thrun, Sebastian Burkhard was born on May 14, 1967 in Solingen, Germany. Son of Winfried and Kristin (Grüner) Thrun.
( Robot motion planning has become a major focus of robot...)
Robot motion planning has become a major focus of robotics. Research findings can be applied not only to robotics but to planning routes on circuit boards, directing digital actors in computer graphics, robot-assisted surgery and medicine, and in novel areas such as drug design and protein folding. This text reflects the great advances that have taken place in the last ten years, including sensor-based planning, probabalistic planning, localization and mapping, and motion planning for dynamic and nonholonomic systems. Its presentation makes the mathematical underpinnings of robot motion accessible to students of computer science and engineering, rleating low-level implementation details to high-level algorithmic concepts.
http://www.amazon.com/gp/product/0262033275/?tag=2022091-20
(Lifelong learning addresses situations in which a learner...)
Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. 'The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm. ' From the Foreword by Tom M. Mitchell.
http://www.amazon.com/gp/product/1461285976/?tag=2022091-20
(Lifelong learning addresses situations in which a learner...)
Lifelong learning addresses situations in which a learner faces a series of different learning tasks providing the opportunity for synergy among them. Explanation-based neural network learning (EBNN) is a machine learning algorithm that transfers knowledge across multiple learning tasks. When faced with a new learning task, EBNN exploits domain knowledge accumulated in previous learning tasks to guide generalization in the new one. As a result, EBNN generalizes more accurately from less data than comparable methods. Explanation-Based Neural Network Learning: A Lifelong Learning Approach describes the basic EBNN paradigm and investigates it in the context of supervised learning, reinforcement learning, robotics, and chess. 'The paradigm of lifelong learning - using earlier learned knowledge to improve subsequent learning - is a promising direction for a new generation of machine learning algorithms. Given the need for more accurate learning methods, it is difficult to imagine a future for machine learning that does not include this paradigm. ' From the Foreword by Tom M. Mitchell.
http://www.amazon.com/gp/product/0792397169/?tag=2022091-20
( Probabilistic robotics is a new and growing area in rob...)
Probabilistic robotics is a new and growing area in robotics, concerned with perception and control in the face of uncertainty. Building on the field of mathematical statistics, probabilistic robotics endows robots with a new level of robustness in real-world situations. This book introduces the reader to a wealth of techniques and algorithms in the field. All algorithms are based on a single overarching mathematical foundation. Each chapter provides example implementations in pseudo code, detailed mathematical derivations, discussions from a practitioner's perspective, and extensive lists of exercises and class projects. The book's Web site, www.probabilistic-robotics.org, has additional material. The book is relevant for anyone involved in robotic software development and scientific research. It will also be of interest to applied statisticians and engineers dealing with real-world sensor data.
http://www.amazon.com/gp/product/0262201623/?tag=2022091-20
researcher computer science educator
Thrun, Sebastian Burkhard was born on May 14, 1967 in Solingen, Germany. Son of Winfried and Kristin (Grüner) Thrun.
Bachelor of Science in Computer Science, Economics and Medicine, University Hildesheim, Germany, 1988. Master of Science in Computer Science and Statistics, University Bonn, Germany, 1993. Doctor of Philosophy summa cum laude in Computer Science and Statistics, University Bonn, Germany, 1995.
Research assistant German National Research Center for Information Technology, Sankt Augustin, Germany, 1989-1991. Project scientist Carnegie Mellon University, Pittsburgh, 1991-1992, research computer scientist, 1995-1998, assistant professor computer science, 1998-2001, associate professor, 2001—2003. Research associate University Bonn, 1993-1995.
Associate professor computer science Stanford University, California, since 2003, associate professor electrical engineering, since 2006. Director Stanford Artificial Intelligence Laboratory, since 2004. Consultant Daimler Benz Research, Berlin, 1995, Real World Interface, Inc., Jaffrey, New Hampshire, 1996.
Vice president development Neural Information Processing Systems Foundation, since 2003.
(Lifelong learning addresses situations in which a learner...)
(Lifelong learning addresses situations in which a learner...)
( Probabilistic robotics is a new and growing area in rob...)
( Robot motion planning has become a major focus of robot...)
Fellow: European Coordinating Committee Artificial Intelligence, American Association Artificial Intelligence (2nd place in autonomous mobile robot competition 1994, 1st place in autonomous mobile robot competition 1996), World Technology Network (World Technical award-Information Technology Software 2006). Member: National Academy of Engineering.
Married Petra Dierkes, July 1, 1995.