Interview with Zack Serlin, MIT Lincoln Laboratories: Formal methods for safe robotic control скачать в хорошем качестве

Interview with Zack Serlin, MIT Lincoln Laboratories: Formal methods for safe robotic control

Interview with Zack Serlin of MIT Lincoln Laboratories who specializes in the use for formal methods for safe robotic control via reinforcement learning. 00:00 Introduction 06:57 Zak discusses how his work in NSAI is different from what we normally talk about 10:04 Formal methods to interpretable RL for robotic planning 28:21 Related work: Boolean task algebra for RL 37:10 Safety aware task composition for discrete and continuous RL 49:09 Closing comments / advice to students looking to do research in robotics and RL Relevant papers: https://www.science.org/doi/10.1126/s... https://arxiv.org/pdf/2306.17033.pdf DISTRIBUTION STATEMENT A. Approved for public release. Distribution is unlimited. This material is based upon work supported by the Under Secretary of Defense for Research and Engineering under Air Force Contract No. FA8702-15-D-0001. Any opinions, findings, conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the Under Secretary of Defense for Research and Engineering. © 2023 Massachusetts Institute of Technology. Delivered to the U.S. Government with Unlimited Rights, as defined in DFARS Part 252.227-7013 or 7014 (Feb 2014). Notwithstanding any copyright notice, U.S. Government rights in this work are defined by DFARS 252.227-7013 or DFARS 252.227-7014 as detailed above. Use of this work other than as specifically authorized by the U.S. Government may violate any copyrights that exist in this work. About the channel: The Neuro Symbolic Channel provides the tutorials, courses, and research results on one of the most exciting areas in artificial intelligence and machine learning. With content originally from the AI course taught at Arizona State University, this channel brings you the latest at the intersection of symbolic methods (e.g., logic programming) and deep learning. Learn about the latest algorithms, Python packages, and progress toward larger goals such as artificial general intelligence (AGI).