Towards Scaling Reinforcement Learning to Massive Populations: Learning Mean-Field Representations
A mean-field RL framework is introduced in which the rewards and transition dynamics depend on the population only through an unknown low-dimensional aggregate statistic, and it is shown that under a fixed neural-network parameter count and optimization budget, learning a low-dimensional population representation impro...
Aditya Makkar, B. Unger, Jeongyeol Kwon et al.
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