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: artificial intelligence, machine learning, autonomous systems, robotics (also called “dry”); and cognitive science, neuroscience, psychology, behavioural economics, ethology (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, contributed talks, poster presentations, workshops, tutorials, and social activities.
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