While games have defined rules, real-world challenges often do not. Dimitri P. Bertsekas undergraduate studies were in engineering at the National Technical University of Athens, Greece. Dimitri Bertsekas is currently visiting us to deliver an exciting lecture series, “CS 691: Topics on Reinforcement Learning” for Spring 2019! He looks forward to exploring the art scene and nature Arizona has to offer. Reinforcement Learning for POMDP: Rollout and Policy Iteration with Application to Sequential Repair Sushmita Bhattacharya, Thomas Wheeler advised by Stephanie Gil, Dimitri P. Bertsekas Research Interests Reinforcement learning, artificial intelligence, optimization, linear and nonlinear programming, data communication networks, parallel and distributed computation Angelia Nedich Professor, Arizona State University Verified email at asu.edu. School of Computing, Informatics, and Decision Systems Engineering, Ph.D. System Science, Massachusetts Institute of Technology, M.S. Above: National Academy of Engineering Member Dimitri Bertsekas writes out an equation at the Brickyard building on Arizona State University's Tempe campus. with remarks by Angelia Nedich (Arizona State University) Keynote Talk. Photographer: Erika Gronek/ASU, Public Service and Bertsekas has spent much of his career — since 1979 — as a faculty member at the Massachusetts Institute of Technology, where he held the position of McAfee Professor of Engineering. I, (2017), and Vol. His work has been recognized with many prestigious awards and honors over the years. When he’s not teaching or researching optimization and control theory, Bertsekas enjoys the visual arts, particularly travel and nature photography. ... She is the co-author of the book entitled “Convex Analysis and Optimization” together with Dimitri Bertsekas and Angelia Nedich. ), where he is currently McAfee Professor of Engineering. The following papers and reports have a strong connection to material in the book, and amplify on its analysis and its range of applications. The REACT Lab hosts visitors for collaborations and to give talks. ARIZONA STATE UNIVERSITY CREDIT: ROBERT MAYFIELD/ASU ... Read more about Our paper on distributed learning for POMDP in a sequential repair setting with Dimitri Bertsekas has been accepted for publication in RAL 2020! Together they form a unique fingerprint. Community Solutions, Global Engineering Education (Study Abroad), Engineering Projects in Community Service (EPICS), Diversity and Inclusion Initiative – DII@FSE, Biological and Health Systems Engineering, Computing, Informatics, and Decision Systems Engineering, Electrical, Computer and Energy Engineering, Engineering of Matter, Transport and Energy, Sustainable Engineering and the Built Environment. Teaching Assistantship. Dimitri Bertsekas Massachusetts Institute of Technology and Arizona State University. ASU's Stephanie Gil wins Sloan Research Fellowship... Read more about I was recently selected as a 2020 Sloan Research Fellow for my work in robotics and communication Our paper on distributed learning for POMDP in a sequential repair setting with Dimitri Bertsekas has been accepted for … CSE 691 - Topics in Reinforcement Learning - ASU Spring 2020 taught by Dr. Dimitri Bertsekas; CSE 591 - Coordination of Multi-Robot Systems - ASU Fall 2019 taught by Dr. Stephanie Gil; CSE 691 - Topics in Reinforcement Learning - ASU Spring 2019 taught by Dr. Dimitri Bertsekas Recent News. of the University of Illinois, Urbana (1974-1979). We discuss issues of parallelization and distributed asynchronous computation for large scale dynamic programming problems. In 2018, he was awarded, jointly with his coauthor John Tsitsiklis, the INFORMS John von Neumann Theory Prize, for the contributions of the research monographs "Parallel and Distributed Computation" and "Neuro-Dynamic Programming". Throughout his career, Dimitri Bertsekas has enjoyed engineering’s rich variety of challenges and how many of them can be viewed through a “unifying mathematical lens.”. Heewook Lee Assistant Professor Computer Science and Engineering. Additionally, he has earned several key awards over the span of 20 years from American Automatic Control Council and from the Institute for Operations Research and the Management Sciences, known as INFORMS, an international society for operations research, management science and analytics professionals. He joins the Ira A. Fulton Schools of Engineering Faculty as the Fulton Chair of Computational Decision Making and will contribute his expertise in optimization and optimal control, reinforcement learning, applied probability, and large-scale computation. Ykobaya@asu.edu (480) 965-3708 Tempe campus, BYENG 354. He obtained his MS in electrical engineering at the George Washington University, Wash. DC in 1969, and his Ph.D. in system science in 1971 at the Massachusetts Institute of Technology. His current work focuses on reinforcement learning, artificial intelligence, optimization, linear and nonlinear programming, data communication networks, parallel and distributed computation. Bertsekas, D., "Multiagent Value Iteration Algorithms in Dynamic Programming and Reinforcement Learning ," arXiv preprint, arXiv:2005.01627, April 2020; to appear in Results in Control and Optimization J. Bertsekas’ passion for education has also won him accolades. In 2019, he was also appointed Fulton Chair of Computational Decision Making at the School of  Computing, Informatics, and Decision Systems Engineering at Arizona State University, Tempe, while maintaining a research position at MIT. AU - Bertsekas, Dimitri P. PY - 1975/12. Thursday, April 26, 2018 2:30 p.m College Avenue Commons (CAVC) 101, Tempe campus . Dimitri P. Bertsekas, a member of the U.S. National Academy of Engineering, is Fulton Professor of Computational Decision Making at Arizona State University, and McAfee Professor of Engineering at Massachusetts Institute of Technology. ASU Web Site. Dimitri Visits REACT Dimitri ASU Talk In addition to controlling teams of robots we also have fun at the REACT Lab. Check out the REACT Lab’s first pizza social! Check out the REACT Lab’s first pizza social! N2 - This paper identifies necessary and sufficient conditions for a penalty method to yield an optimal solution or a Lagrange multiplier of a convex programming problem by means of a single unconstrained minimization. Bertsekas has written numerous research papers and 17 books and research monographs on the topics of optimization theory and algorithms, dynamic programming and optimal control, data communications, parallel and distributed computation, and applied probability. In addition to controlling teams of robots we also have fun at the REACT Lab. Dimitri Bertsekas: Permission (Reusing this file) Permitted by Dimitri Bertsekas: Licensing .