The 2025 Multi-disciplinary Conference on Reinforcement Learning and Decision Making (RLDM) will be held on June 11-14, 2025 at Trinity College Dublin, Ireland.

SUBMISSIONS
Submissions open November 1 2024
Workshop submission deadline December 10 2024
Abstract submission deadlineJanuary 15 2025
Travel award submission deadline January 15 2025
NOTIFICATIONS
Workshop notificationJanuary 10 2025
Abstract, Talk and Spotlight notificationFebruary 15 2025
Travel award notification February 20 2025

RLDM is an interdisciplinary, non-archival conference about learning and decision making in humans, animals, and algorithms, with a particular focus on approaches based on reinforcement learning. RLDM is unique in its effort to bring together researchers working in/with reinforcement learning from two broadly-defined communities: AI, machine learning, autonomous systems, robotics (also called “dry”); and cognitive science, neuroscience, psychology, behavioural economics (also called “wet”). RLDM was previously held in Princeton (2013), Edmonton (2015), Ann Arbor (2017), Montreal (2019), and Providence (2022). The program consists of a mix of invited talks, paper presentations, workshops, tutorials, and social activities.

General Chair
Roshan Cools, Radboud University Nijmegen

Program Chairs
Anne GE Collins, University of California, Berkeley
Stefano V. Albrecht, University of Edinburgh

Local Chairs
Claire Gillan, Trinity College Dublin
Redmond O’Connell, Trinity College Institute of Neuroscience and School of Psychology

Review Chairs
Sam Devlin, Microsoft Research Cambridge
Matt Nassar, Brown University

Workshop Chairs
David Abel, Google DeepMind London
Hanneke den Ouden, Radboud University Nijmegen

Tutorial Chairs
Amy Zhang, University of Texas at Austin
Angela Langdon, National Institute of Mental Health

Mentoring Chairs
Reuth Mirsky, Tufts University
Bob Wilson, Georgia Institute of Technology

Social Chair
Sam McDougle, Yale University

Fundraising Chair
Marcello Restelli, Politecnico di Milano

Executive Committee
Yael Niv, Princeton University
Peter Dayan, Max Planck Institute for Biological Cybernetics
Cate Hartley, New York University
Richard Sutton, University of Alberta
Peter Stone, University of Texas at Austin
Satinder Singh, Google DeepMind & University of Michigan