Reminder that the deadline for the Finding the Frame workshop @RL_Conference is coming up on May 22 AoE ⏰
We're excited to read your submissions reflecting on the philosophy, practice, and formalisms of reinforcement learning!
🔗 More details: https://t.co/mNy0SGK1H2
Reminder that the deadline for the Finding the Frame workshop @RL_Conference is coming up on May 22 AoE ⏰
We're excited to read your submissions reflecting on the philosophy, practice, and formalisms of reinforcement learning!
🔗 More details: https://t.co/mNy0SGK1H2
Finding the Frame will be back at @RL_Conference 2026 with a fantastic speaker lineup! We welcome submissions that reflect on the philosophy, practice, and formalisms of reinforcement learning.
📅Submission deadline: May 22, 2026 (AoE)
More details: https://t.co/bYbIW3QKB7
Thanks to everyone who joined us for another great workshop! 🥳
This year we once again asked our panelists to share a paper or book that heavily influenced their perspective 📚 check out their recommendations here! https://t.co/ZVfbTWk0lg
We will conclude with a discussion of alternative assumptions which might be more friendly to the development of agents capable of the open-ended, iterative, and creative intelligent behaviours necessary for pushing the frontier of human knowledge.
Completing our fantastic lineup of invited talks is Dr. @clarelyle (Deepmind) who will speak on Beyond Optimality: Designing Open-Ended RL Agents. Abstract in 🧵
such as the distinction between the agent and environment, the stationarity of the environment transition dynamics, and the external source of reward, influence the types of behaviour we can expect to observe in our agents.
Reinforcement learning studies systems that generate reward-maximizing behavior. Where does the idea of a mind fit into this picture, if it’s even needed? Should we be behaviorists, cognitivists, or something in between?
and that therefore 3) a critical component for achieving general intelligence is the ability to autonomously construct task-specific frames, which can be achieved by learning mutually-compatible observation and action abstractions.
We have a really exciting lineup of invited speakers this year 🔥 Kicking us off we have Prof. Erin Talvitie (Harvey Mudd College), whose talk is titled: 20 Years of Asking the Wrong Questions in Model-based reinforcement learning. Abstract in 🧵
And yet, making sustained, robust progress toward this goal has proved surprisingly, infuriatingly difficult. We'll take a high-level tour of some garden paths and blind alleys that have caused useful shifts in my own frame,