RLDM 2019


Hyperbolic Discounting and Learning over Multiple Horizons
Liam Fedus, Carles Gelada, Yoshua Bengio, Marc G. Bellemare
Hugo Larochelle

A distributional code for value in dopamine-based reinforcement learning
Will Dabney, Zeb Kurth-Nelson, Naoshige Uchida, Clara Kwon Starkweather
Demis Hassabis, Remi Munos, Matthew Botvinick


Schedule at a Glance

Program Brochure

Conference Sponsors

Talk and Poster Abstracts

Reinforcement learning and decision making have been the focus of research spanning a wide variety of fields including psychology, artificial intelligence, machine learning, operations research, control theory, animal and human neuroscience, economics, and ethology. Key to many developments in the field has been interdisciplinary sharing of ideas and findings. RLDM is the only conference that brings all these communities together.

The focus of the conference can be broadly construed as decision making over time to achieve a goal. Our aim is to create a recurring meeting characterized by the multidisciplinarity of the presenters and attendees, with cross-disciplinary conversations and teaching and learning being central objectives along with the dissemination of novel theoretical and experimental results.

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