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 deadline | January 15 2025 |
Travel award submission deadline | January 15 2025 |
NOTIFICATIONS | |
Workshop notification | January 10 2025 |
Abstract, Talk and Spotlight notification | February 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