Podcast "inControl"

The first podcast on control theory and related topics, including feedback, decision making, artificial intelligence, robotics and much more. The podcast is supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» at ETH Zürich, which you can check at the following link: https://nccr-automation.ch/nccr-automation

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Podcast "inControl"

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ep3 - Ben Recht: A tour of optimization, machine learning, and control

In this episode, our guest is Ben Recht. Ben is a Professor in the Department of Electrical Engineering and Computer Sciences at the University of California, Berkeley.  We discuss several topics, including his research trajectory, Ben's tour of reinforcement learning, and his passion for music, among others. Check out Ben's website here: http://people.eecs.berkeley.edu/~brecht/Outline00:00 - Intro 01:01 - Ben predicts the birth of "inControl"02:40 - Personal research trajectory06:55 - How and why did you dive into control theory?08:43 - Influential figures who shaped Ben's research13:50 -  The "argmin" blog &  myth busting27:43 - Ben's tour of reinforcement learning45:18 - Future challenges for control52:06 - Biological origin of learning58:24 - "This or that" game1:02:54 - Questions from the audience1:14:51 - What would you do if you were a student today?1:17:00 - Ben's band: "the fun years"Episode linksBen's website: http://people.eecs.berkeley.edu/~brecht/argmin: http://www.argmin.net/the fun years: http://thefunyears.com/A tour of reinforcement learning: https://arxiv.org/abs/1806.09460Patterns, predictions and actions: http://mlstory.org/System level synthesis: https://arxiv.org/abs/1904.01634 Aizerman's conjecture: https://en.wikipedia.org/wiki/Aizerman%27s_conjecturePodcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://podcasts.apple.com/us/podcast/incontrol/id1624068002Spotify: https://open.spotify.com/show/7dZvt77XNtHxyrFqM8YTwfRSS: https://feeds.buzzsprout.com/1632769.rssYoutube: https://www.youtube.com/channel/UCl83hwBSVRLYj2NWS08P9bg/featuredFacebook: https://www.facebook.com/InControl-podcast-114303337936834Twitter: https://twitter.com/IncontrolPInstagram: https://www.instagram.com/incontrol_podcast/Patreon: https://www.patreon.com/incontrolpodcast/Acknowledgments and sponsorsThis episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation», which you can check here:https://nccr-automation.ch/nccr-automationThe podcast benefits from the help of an incredibly talented and passionate team. Special thanks to Arian Bastani, Benjamin Sawicki, Elise Cahard, Florian Dorfler, Frederik Banis, John Lygeros, ETH studio (Philipp Zumbrunnen), and mirrorlake studio (Roman Frischknecht). The support of the Swiss National Science Foundation is also gratefully acknowledged. Music was composed by A New Element.Support the show

Erschienen: 16.05.2022
Dauer: 01:21:34

Weitere Informationen zur Episode "ep3 - Ben Recht: A tour of optimization, machine learning, and control"


ep 5 - Sean Meyn: Markov chains, networks, reinforcement learning, beekeeping and jazz

In this episode, our guest is Sean Meyn, Professor and Robert C. Pittman Eminent Scholar Chair in the Department of Electrical and Computer Engineering at the University of Florida. The episode features Sean’s adventures in the areas of Markov chains, networks and Reinforcement Learning (RL) as well as anecdotes and trivia about beekeeping and jazz.Outline00:00 - Intro00:22 - Sean’s early steps03:53 - Markov chains08:45 - Networks18:26 - Stochastic approximation25:00 - Reinforcement Learning38:57 - The intersection of Reinforcement Learning and  Control42:37 - Favourite theorem44:05 - Beekeeping and jazz48:47 - OutroEpisode linksSean’s website: https://meyn.ece.ufl.edu/Sean’s books: shorturl.at/CFGRY (and T. Sargent's review: shorturl.at/hlGNR)G. Zames: shorturl.at/JPRWX (see also: shorturl.at/chiw5)State space model: shorturl.at/hST07 The life and work of A.A. Markov: shorturl.at/qsv35Fluid model: shorturl.at/HKN56M/M/1 queue: shorturl.at/dQW36Borkar-Meyn theorem: shorturl.at/eSTV4NCCR Automation Symposia: shorturl.at/csv03 (see also shorturl.at/ekpZ3)V. Konda’s PhD Thesis: shorturl.at/bdrv7Podcast infoPodcast website: https://www.incontrolpodcast.com/ Apple Podcasts: https://podcasts.apple.com/us/podcast/incontrol/id1624068002 Spotify: https://open.spotify.com/show/7dZvt77XNtHxyrFqM8YTwf RSS: https://feeds.buzzsprout.com/1632769.rss Youtube: https://www.youtube.com/channel/UCl83hwBSVRLYj2NWS08P9bg/featured Facebook: https://www.facebook.com/InControl-podcast-114303337936834 Twitter: https://twitter.com/IncontrolP Instagram: https://www.instagram.com/incontrol_podcast/ Patreon: https://www.patreon.com/incontrolpodcast/Acknowledgments and sponsorsThis episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund.The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to A. Bastani, B. Sawicki, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, as well as the ETH  and mirrorlake studios. Music was composed by A New Element.Support the show

Erschienen: 18.08.2022
Dauer: 00:53:22

Weitere Informationen zur Episode "ep 5 - Sean Meyn: Markov chains, networks, reinforcement learning, beekeeping and jazz"


ep 7 - Jean-Jacques Slotine: Sliding, nonlinear and adaptive control, contraction theory, complex networks, optimization, and machine learning

In this episode, our guest is Jean-Jacques Slotine, Professor of Mechanical Engineering and Information Sciences as well as Brain and Cognitive Sciences, Director of the Nonlinear Systems Laboratory at the Massachusetts Institute of Technology, and Distinguished Faculty at Google AI.  We explore and connect a wide range of ideas from nonlinear and adaptive control to robotics, neuroscience, complex networks, optimization and machine learning.Outline00:00 - Intro00:50 - Jean-Jacques' early life06:17 - Why control? 09:45 - Sliding control and adaptive nonlinear control18:47 - Neural networks 23:15 - First ventures in neuroscience28:27 - Contraction theory and applications48:26 - Synchronization51:10 - Complex networks57:59 - Optimization and machine learning1:08:17 -  Advice to future students and outro Episode linksNCCR Symposium: https://tinyurl.com/bdz84p4c Sliding mode control: https://tinyurl.com/2s45ra4mApplied nonlinear control: https://tinyurl.com/4wmbt4bwOn the Adaptive Control of Robot Manipulators: https://tinyurl.com/b7jcpkzwGaussian Networks for Direct Adaptive Control: https://tinyurl.com/22zb7pkxThe intermediate cerebellum may function as a wave-variable processor: https://tinyurl.com/2c34ytepOn contraction analysis for nonlinear systems: https://tinyurl.com/5cw4z9j8Kalman conjecture: https://tinyurl.com/2pfjsbkeI. Prigogine: https://tinyurl.com/5ct8yssb RNNs of RNNs: https://tinyurl.com/3mpt7fecHow Synchronization Protects from Noise: https://tinyurl.com/2p82erwp Controllability of complex networks: https://tinyurl.com/24w7hdaeB. Anderson: https://tinyurl.com/e9pkyxdxOnline lectures on nonlinear control: https://tinyurl.com/525cnru4Podcast infoPodcast website: https://www.incontrolpodcast.com/Apple Podcasts: https://tinyurl.com/5n84j85jSpotify: https://tinyurl.com/4rwztj3cRSS: https://feeds.buzzsprout.com/1632769.rssYoutube: https://tinyurl.com/bdbvhsj6Facebook: https://tinyurl.com/3z24yr43Twitter: https://twitter.com/IncontrolPInstagram: https://www.instagram.com/incontrol_podcast/Acknowledgments and sponsorsThis episode was supported by the National Centre of Competence in Research on «Dependable, ubiquitous automation» and the IFAC Activity fund.The podcast benefits from the help of an incredibly talented and passionate team. Special thanks to B. Seward, E. Cahard, F. Banis, F. Dörfler, J. Lygeros, as well as the ETH and mirrorlake studios.Music was composed by A New Element. Support the show

Erschienen: 29.11.2022
Dauer: 01:10:57

Weitere Informationen zur Episode "ep 7 - Jean-Jacques Slotine: Sliding, nonlinear and adaptive control, contraction theory, complex networks, optimization, and machine learning"


Podcast "inControl"
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