All Episodes

Displaying episodes 31 - 53 of 53 in total

Marc G. Bellemare

Marc G. Bellemare shares insight on his work including Deep Q-Networks, Distributional RL, Project Loon and RL in the Stratosphere, the origins of the Arcade Learning ...

Robert Osazuwa Ness

Dr. Robert Osazuwa Ness on Causal Inference, Probabilistic and Generative Models, Causality and RL, AltDeep School of AI, Pyro, and more!

Marlos C. Machado

Marlos C. Machado on Arcade Learning Environment Evaluation, Generalization and Exploration in RL, Eigenoptions, Autonomous navigation of stratospheric balloons with R...

Nathan Lambert

Nathan Lambert on Model-based RL, Trajectory-based models, Quadrotor control, Hyperparameter Optimization for MBRL, RL vs PID control, and more!

Kai Arulkumaran

Kai Arulkumaran on AlphaStar and Evolutionary Computation, Domain Randomisation, Upside-Down Reinforcement Learning, Araya, NNAISENSE, and more!

Michael Dennis

Michael Dennis on Human-Compatible AI, Game Theory, PAIRED, ARCTIC, EPIC, and lots more!

Roman Ring

Roman Ring discusses the Research Engineer role at DeepMind, StarCraft II, AlphaStar, his bachelor's thesis, JAX, Julia, IMPALA and more!

Shimon Whiteson

Shimon Whiteson on his WhiRL lab, his work at Waymo UK, variBAD, QMIX, co-operative multi-agent RL, StarCraft Multi-Agent Challenge, advice to grad students, and much ...

Aravind Srinivas

Aravind Srinivas on his work including CPC v2, RAD, CURL, and SUNRISE, unsupervised learning, teaching a Berkeley course, and more!

Taylor Killian

Taylor Killian on the latest in RL for Health, including Hidden Parameter MDPs, Mimic III and Sepsis, Counterfactually Guided Policy Transfer and lots more!

Nan Jiang

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

Danijar Hafner takes us on an odyssey through deep learning & neuroscience, PlaNet, Dreamer, world models, latent dynamics, curious agents, and more!

Csaba Szepesvari

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

Ben Eysenbach schools us on human supervision, SORB, DIAYN, techniques for exploration, teaching RL, virtual conferences, and much more!

NeurIPS 2019 Deep RL Workshop

Hear directly from presenters at the NeurIPS 2019 Deep RL Workshop on their work!

Scott Fujimoto

Scott Fujimoto expounds on his TD3 and BCQ algorithms, DDPG, Benchmarking Batch RL, and more!

Jessica Hamrick

Jessica Hamrick sheds light on Model-based RL, Structured agents, Mental simulation, Metacontrol, Construction environments, Blueberries, and more!

Pablo Samuel Castro

Pablo Samuel Castro drops in and drops knowledge on distributional RL, bisimulation, the Dopamine RL Framework, TF-Agents, and much more!

Kamyar Azizzadenesheli

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

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 an...

Michael Littman

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,...

Natasha Jaques

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 Goog...

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