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[P] Reinforcement Learning / Game Theory on Urban Planning Problems


I’ve been working on the use of machine learning models for urban planning problems for my PhD. My earlier work focused on the use of regression-based models (ANN, GPR, etc.) but due to changes in funding, I’m having to switch to reinforcement learning / game theoretic models for my current work. However, I haven’t been able to find collaborators from the RL domain in my university, and my advisor is not an expert in it either.

Our project currently involves path planning or resource allocation in stochastic environments (eg: snow plowing, police placement [not predictive policing], trash pickup, etc.). If there is anyone in this sub-reddit who has experience in these domains or RL in general, and if you’re interested to collaborate, please reach out.

I could try and do a lot of literature surveys to make sure I’m not trying to reinvent a wheel or going in the wrong direction, but I strongly believe that subject experts would be able to provide much better insights.

submitted by /u/AdmiralLunatic
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.