Scaling Reinforcement Learning to Infinite Agents Using Mean Field Games

The relatively unknown game theory method might hold the key to massively scalable reinforcement learning systems.

Jesus Rodriguez
DataSeries

--

Source: https://www.microsoft.com/en-us/research/blog/winners-announced-in-multi-agent-reinforcement-learning-challenge/

I recently started a new newsletter focus on AI education. TheSequence is a no-BS( meaning no hype, no news etc) AI-focused newsletter that takes 5 minutes to read. The goal is to keep you up to date with machine learning projects, research papers and concepts. Please give it a try by subscribing below:

Reinforcement learning is one of the most popular areas of research in deep learning nowadays. Part of the popularity of reinforcement learning is due to the fact that is one of the learning methods that resembles human cognition the closets. In reinforcement learning scenarios and agent learns organically by taking actions on an environment and receiving specific rewards. A little less known discipline called multi-agent reinforcement learning(MARL) focuses on reinforcement learning scenarios involving a large number of agents. Typically, MARL…

--

--

Jesus Rodriguez
DataSeries

CEO of IntoTheBlock, President of Faktory, President of NeuralFabric and founder of The Sequence , Lecturer at Columbia University, Wharton, Angel Investor...