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Finding the Frame
  • Home
  • Schedule
  • Submission Guide
  • Accepted Papers
  • Resources
  • Past Years
    • 2024
      • Schedule
      • Recordings
      • Accepted Papers
      • Submission Guide
      • Resources
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    • Home
    • Schedule
    • Submission Guide
    • Accepted Papers
    • Resources
    • Past Years
      • 2024
        • Schedule
        • Recordings
        • Accepted Papers
        • Submission Guide
        • Resources

Finding the Frame 

An RLC Workshop for Examining Conceptual Frameworks in RL

August 05, 2025

About

Scientific research is often framed within paradigms of concepts, definitions, axioms, and assumptions — RL is no exception. While such details usually go unchallenged in the pursuit of specific objectives, this workshop brings them into sharp focus. In this workshop, we examine the conceptual foundations of RL and their impact on framing problems. We are excited for this workshop, because we believe it has the potential to open up new territory, test our historical beliefs, and ultimately guide our future research endeavors in productive directions. Overall, we hope to generate enthusiasm and build a community dedicated to examining the conceptual foundations of RL.

This is a full-day workshop. The first half of the day features four short talks, representing different perspectives on RL. Following these talks, these speakers join a panel discussion. Using this panel as backdrop for the rest of the day, we open the floor to submitted work, which includes poster sessions and lightning talks.  (See the detailed schedule.)

Call for Papers

Topics. We invite submission of papers that reflect on the philosophy, practice, and formalisms of reinforcement learning. This includes, but is not limited to, the following areas: 


  • Proposals that explore beyond the standard RL problem or paradigm.

  • Any work rethinking goals, models, values, or rewards in the context of RL.

  • Novel benchmarks or applications that explore limitations of our previous paradigms.

  • Reflections on the basic building blocks or methods of reinforcement learning.

  • Detailed analysis to expose issues with existing challenges and benchmarks that artificially or deceptively narrow the RL frame. 

  • Work that examines the underlying formulations or assumptions of RL implicit in current solution approaches.

  • Methods that address new paradigms, where a significant portion of the paper focuses on the novel paradigm. See this paper as an example.

  • Philosophy of science in RL.



We also welcome submissions that interpret our theme in other creative ways. Though this year’s theme is slightly different, see the accepted paper list from Finding the Frame 2024 for an idea of how this theme was previously interpreted.



Formatting. There is a page limit of seven content pages (excluding the references, acknowledgements, and appendices). All submissions should be in the RLC format; see the submission guide for more details.

Dual Submissions. Work that is in submission or under review at a conference or journal is welcome. We are not accepting already-published work.

Important Dates

Submission deadline:  15 June, 2025 (Anywhere on Earth)

Acceptance notification: 30 June,  2025

Camera-ready submission deadline: TBD, 2025

Workshop date: 05 August 2025


Speakers/Panelists

Erin Talvitie

(Harvey Mudd College)

George Konidaris

(Brown University)

Mark Ho

(NYU)

Clare Lyle

(Google DeepMind)

Organizers

Alex Lewandowski

(Amii / University of Alberta)

Aly Lidayan

(BAIR/UC Berkeley)

Stephanie Milani

(CMU)

Prabhat Nagarajan
(Amii / University of Alberta)

Johan Obando-Ceron

(Mila / University of Montreal)

Andi Peng

(Anthropic/MIT CSAIL)

Esra'a Saleh
(Mila / University of Montreal)

Advisory Committee

David Abel
(Google DeepMind / University of Edinburgh)

Michael Dennis
(Google DeepMind)

Taylor Killian
(University of Toronto)

John D. Martin
(Openmind Research Institute / University of Alberta)

We can be contacted at findingtheframeworkshop at gmail dot com 

or @ us on X/Twitter at @RLFrameWorkshop


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