Nan Jiang takes us deep into Model-based vs Model-free RL, Sim vs Real, Evaluation & Overfitting, RL Theory vs Practice and much more!
Danijar Hafner takes us on an odyssey through deep learning & neuroscience, PlaNet, Dreamer, world models, latent dynamics, curious agents, and more!
Csaba Szepesvari of DeepMind shares his views on Bandits, Adversaries, PUCT in AlphaGo / AlphaZero / MuZero, AGI and RL, what is timeless, and more!
Ben Eysenbach schools us on human supervision, SORB, DIAYN, techniques for exploration, teaching RL, virtual conferences, and much more!
Hear directly from presenters at the NeurIPS 2019 Deep RL Workshop on their work!
Scott Fujimoto expounds on his TD3 and BCQ algorithms, DDPG, Benchmarking Batch RL, and more!
Jessica Hamrick sheds light on Model-based RL, Structured agents, Mental simulation, Metacontrol, Construction environments, Blueberries, and more!
Pablo Samuel Castro drops in and drops knowledge on distributional RL, bisimulation, the Dopamine RL Framework, TF-Agents, and much more!
Kamyar Azizzadenesheli brings us insight on Bayesian RL, Generative Adversarial Tree search, what goes into great RL papers, and much more!
Antonin Raffin and Ashley Hill discuss Stable Baselines past, present and future, State Representation Learning, S-RL Toolbox, RL on real robots, big compute for RL and much more!
ACM Fellow Professor Michael L Littman enlightens us on Human feedback in RL, his Udacity courses, Theory of Mind, organizing the RLDM Conference, RL past and present, Hollywood cameos, and much more!
Natasha Jaques talks about her PhD, her papers on Social Influence in Multi-Agent RL, ML & Climate Change, Sequential Social Dilemmas, internships at DeepMind and Google Brain, Autocurricula, and more!
Introducing TalkRL Podcast! Also check out our website at talkRL.com
(c) 2019 Robin Ranjit Singh Chauhan