1 citations · 1 across the 3 of their papers we have counts for
3 papers
Sorrel: A simple and flexible framework for multi-agent reinforcement learning
Rebekah A. Gelpí, Yibing Ju, Ethan C. Jackson +4
We introduce Sorrel (https://github.com/social-ai-uoft/sorrel), a simple Python interface for generating and testing new multi-agent reinforcement learning environments. This inter…
Food for thought: How can machine learning help better predict and understand changes in food prices?
Kristina L. Kupferschmidt, James Requiema, Mya Simpson +5
In this work, we address a lack of systematic understanding of fluctuations in food affordability in Canada. Canada's Food Price Report (CPFR) is an annual publication that predict…
Temporal-Difference Learning Using Distributed Error Signals
Jonas Guan, Shon Eduard Verch, Claas Voelcker +3
A computational problem in biological reward-based learning is how credit assignment is performed in the nucleus accumbens (NAc). Much research suggests that NAc dopamine encodes t…