TalkRL: The Reinforcement Learning Podcast cover image

TalkRL: The Reinforcement Learning Podcast

Latest episodes

undefined
7 snips
Mar 9, 2025 • 10min

NeurIPS 2024 - Posters and Hallways 3

Posters and Hallway episodes are short interviews and poster summaries.  Recorded at NeurIPS 2024 in Vancouver BC Canada.   Featuring  Claire Bizon Monroc from Inria: WFCRL: A Multi-Agent Reinforcement Learning Benchmark for Wind Farm Control  Andrew Wagenmaker from UC Berkeley: Overcoming the Sim-to-Real Gap: Leveraging Simulation to Learn to Explore for Real-World RL  Harley Wiltzer from MILA: Foundations of Multivariate Distributional Reinforcement Learning  Vinzenz Thoma from ETH AI Center: Contextual Bilevel Reinforcement Learning for Incentive Alignment  Haozhe (Tony) Chen & Ang (Leon) Li from Columbia: QGym: Scalable Simulation and Benchmarking of Queuing Network Controllers  
undefined
Mar 5, 2025 • 9min

NeurIPS 2024 - Posters and Hallways 2

Dive into cutting-edge research from NeurIPS 2024! Explore how cultural accumulation enhances generational intelligence in reinforcement learning. Discover innovations in training device-control agents through autonomous methods, outperforming traditional techniques. Learn about improving stability and convergence in deep reinforcement learning, tackling state-action churn effectively. Finally, uncover versatile methodologies and tools that boost efficiency across various algorithms, featuring the impressive JackSmile resource.
undefined
Mar 3, 2025 • 10min

NeurIPS 2024 - Posters and Hallways 1

This discussion dives into innovative methods for unsupervised skill discovery in hierarchical reinforcement learning, using driving as a practical example. It also tackles trust issues in Proximal Policy Optimization and introduces Time-Constrained Robust MDPs for improved performance. Sustainability in supercomputing is highlighted, showcasing AI's role in reducing energy consumption. Additionally, there's a focus on standardizing multi-agent reinforcement learning for better control and optimizing exploration strategies when rewards are not easily visible.
undefined
Feb 10, 2025 • 1h 22min

Abhishek Naik on Continuing RL & Average Reward

Abhishek Naik, a postdoctoral fellow at the National Research Council of Canada, recently completed his PhD in reinforcement learning under Rich Sutton. He explores average reward methods and their implications for continuous decision-making in AI. The discussion dives into innovative applications in space exploration and challenges in resource allocation, drawing on examples like Mars rovers. Abhishek emphasizes the transformative power of first-principles thinking, highlighting how AI advancements are shaping the future of spacecraft control and missions.
undefined
Dec 23, 2024 • 18min

Neurips 2024 RL meetup Hot takes: What sucks about RL?

What do RL researchers complain about after hours at the bar?  In this "Hot takes" episode, we find out!  Recorded at The Pearl in downtown Vancouver, during the RL meetup after a day of Neurips 2024.  Special thanks to "David Beckham" for the inspiration :)  
undefined
Sep 20, 2024 • 13min

RLC 2024 - Posters and Hallways 5

David Radke from the Chicago Blackhawks shares insights on using reinforcement learning in professional sports to enhance team performance. Abhishek Naik discusses the significance of continuing reinforcement learning and average reward, sparking a conversation about adaptability in AI. Daphne Cornelisse dives into autonomous driving and multi-agent systems, focusing on how to improve human-like behavior. Shray Bansal examines cognitive bias in human-AI teamwork, while Claas Voelcker tackles the complexities of hopping in reinforcement learning. Each guest brings a unique perspective on cutting-edge research.
undefined
Sep 19, 2024 • 5min

RLC 2024 - Posters and Hallways 4

David Abel from DeepMind dives into the 'Three Dogmas of Reinforcement Learning,' offering fresh insights on foundational principles. Kevin Wang from Brown discusses innovative variable depth search methods for Monte Carlo Tree Search, enhancing efficiency. Ashwin Kumar from Washington University addresses fairness in resource allocation, highlighting ethical implications. Finally, Prabhat Nagarajan from UAlberta delves into Value overestimation, revealing its impact on decision-making in RL. This dynamic conversation touches on pivotal advancements and challenges in the field.
undefined
Sep 18, 2024 • 7min

RLC 2024 - Posters and Hallways 3

Posters and Hallway episodes are short interviews and poster summaries.  Recorded at RLC 2024 in Amherst MA.  Featuring:  0:01 Kris De Asis from Openmind on Time Discretization  2:23 Anna Hakhverdyan from U of Alberta on Online Hyperparameters  3:59 Dilip Arumugam from Princeton on Information Theory and Exploration  5:04 Micah Carroll from UC Berkeley on Changing preferences and AI alignment  
undefined
Sep 16, 2024 • 16min

RLC 2024 - Posters and Hallways 2

Posters and Hallway episodes are short interviews and poster summaries.  Recorded at RLC 2024 in Amherst MA.  Featuring:  0:01 Hector Kohler from Centre Inria de l'Université de Lille with "Interpretable and Editable Programmatic Tree Policies for Reinforcement Learning"  2:29 Quentin Delfosse from TU Darmstadt on "Interpretable Concept Bottlenecks to Align Reinforcement Learning Agents"  4:15 Sonja Johnson-Yu from Harvard on "Understanding biological active sensing behaviors by interpreting learned artificial agent policies"  6:42 Jannis Blüml from TU Darmstadt on "OCAtari: Object-Centric Atari 2600 Reinforcement Learning Environments"  8:20 Cameron Allen from UC Berkeley on "Resolving Partial Observability in Decision Processes via the Lambda Discrepancy"  9:48 James Staley from Tufts on "Agent-Centric Human Demonstrations Train World Models"  14:54 Jonathan Li from Rensselaer Polytechnic Institute  
undefined
Sep 10, 2024 • 6min

RLC 2024 - Posters and Hallways 1

Posters and Hallway episodes are short interviews and poster summaries.  Recorded at RLC 2024 in Amherst MA.  Featuring:  0:01 Ann Huang from Harvard on Learning Dynamics and the Geometry of Neural Dynamics in Recurrent Neural Controllers  1:37 Jannis Blüml from TU Darmstadt on HackAtari: Atari Learning Environments for Robust and Continual Reinforcement Learning  3:13 Benjamin Fuhrer from NVIDIA on Gradient Boosting Reinforcement Learning  3:54 Paul Festor from Imperial College London on Evaluating the impact of explainable RL on physician decision-making in high-fidelity simulations: insights from eye-tracking metrics  

Get the Snipd
podcast app

Unlock the knowledge in podcasts with the podcast player of the future.
App store bannerPlay store banner

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode

Save any
moment

Hear something you like? Tap your headphones to save it with AI-generated key takeaways

Share
& Export

Send highlights to Twitter, WhatsApp or export them to Notion, Readwise & more

AI-powered
podcast player

Listen to all your favourite podcasts with AI-powered features

Discover
highlights

Listen to the best highlights from the podcasts you love and dive into the full episode