Continual RL Workshop

♾ Thank you all for your attendance and perspectives that make the first-ever Continual RL workshop so special. ⏳ Stay tuned: more beautiful photos and recordings coming soon…

⏳2 days away => Continual RL Workshop! Finally, let’s welcome Richard S. Sutton, Founder and Research Scientist at Oak Lab and Professor at the University of Alberta. 🎙️Talk: Generate-and-test methods for Continual Learning

Please check out Rich’s personal website to learn more about him and his work 👇 incompleteideas.net

🚨 3 days until Continual RL Workshop! Happy to welcome Katia Sycara, Research Professor at Carnegie Mellon University. 🎙️Talk: Long Horizon Reasoning via Neurosymbolic Learning

Katia’s (www.cs.cmu.edu/~sycara/) research spans broadly across multi-agent systems, human-robot interactions, game theoretic techniques, adversarial reasoning, machine learning, case-based reasoning, planning and scheduling, large scale human-machine systems, and etc.

Thrilled to introduce Peter Stone, Professor at The University of Texas at Austin and Chief Scientist of Sony AI. 🎙️Talk: Continual RL and Automatic Curriculum Learning

Peter (www.cs.utexas.edu/~pstone) aims to understand how to best create complete intelligent agents. He considers adaptation, interaction, and embodiment to be essential capabilities of such agents. His research focuses mainly on machine learning, multiagent systems, and robotics.

⏳ Another day closer — just 5 days to the Continual RL Workshop! Excited to introduce George Konidaris, professor at Brown University and co-founder of two technology startups. 🎙️Talk: Resolving the Sensorimotor Dilemma

George (cs.brown.edu/people/gdk) aims to build intelligent, autonomous, general-purpose robots that are generally capable in a wide variety of tasks and environments. He focuses on understanding how to design agents that learn abstraction hierarchies that enable fast, goal-oriented planning.

⏳ 6 days to go! Joining us is A. Rupam Mahmood, Associate Professor at the University of Alberta and Amii. 🎙️Talk: Three Challenges of Continual Reinforcement Learning

Rupam (armahmood.github.io) works to understand scalable and general learning mechanisms for continually improving agents. To this end, he develops continual reinforcement and representation learning algorithms and real-time learning systems, including for controlling physical robots.

🚨 7 days until Continual RL Workshop! Meet our next speaker: Sarath Chandar @sarath-chandar.bsky.social , Associate Professor at Polytechnique Montréal and Mila. 🎙️Talk: Stable Adaptation Under Distribution Shift

Sarath (sarathchandar.in) works in machine learning, and his long-term vision is to develop interactive learning algorithms that can continually learn from experiences.

🚨 The Continual RL Workshop is coming next Saturday! Excited to introduce our first speaker: David Abel @dabelcs.bsky.social , Staff Research Scientist at Google DeepMind on the Agency team and Honorary Fellow at the University of Edinburgh. 🎙️Title: “Where is Learning?”

🧠 David’s research focuses on understanding the foundations of agency, learning, and computation. He works primarily with the RL problem, drawing on tools and perspectives from philosophy, mathematics, and computer science.

🚨 The Continual RL Workshop is coming next Saturday! Excited to introduce our first speaker: David Abel @dabelcs.bsky.social , Staff Research Scientist at Google DeepMind on the Agency team and Honorary Fellow at the University of Edinburgh. 🎙️Title: “Where is Learning?”

📚 Interested in Continual RL but not sure where to start? 👇 Dive in: sites.google.com/view/continu... ♾️ We've curated a resource hub with key papers, benchmarks, codebases, tutorials, and more to help you get up to speed quickly. #ContinualRL #ReinforcementLearning #MachineLearning #AI

Standard RL assumes a stable world. The real world may not. ♾ Introducing the Continual RL Workshop @rl-conference.bsky.social 2026, Montreal, Canada. 🤖 Agents that learn, adapt, and evolve under constant change. 🖼️ Site: sites.google.com/view/continu... 📄 Submit: sites.google.com/view/continu...

Topics include, but are not limited to different aspects of CRL: 🧠 Foundation & theory ⚙️ Algorithms 🧪 Experimental protocols & benchmarks 🚀 Applications Format: 📑 Papers: 4–8 content pages