The approach avoids scalability limits of traditional dynamic programming.
Jakob Foerster#139
Mean Field Games provide a framework for modelling large populations. ICML26 Spotlight: Introducing Recurrent Structural Policy Gradient for partially observable MFGs with common noise, benefitting from faster convergence than model-free RL, but remaining tractable, unlike DP.
I absolutely loved this interdisciplinary collaboration with the brilliant @ClarisseWibault, @j_foerst and many others at @FLAIR_Ox!
"Recurrent Structural Policy Gradient for Partially Observable Mean Field Games"
Mean Field Games provide a framework for modelling large populations. ICML26 Spotlight: Introducing Recurrent Structural Policy Gradient for partially observable MFGs with common noise, benefitting from faster convergence than model-free RL, but remaining tractable, unlike DP.
The approach avoids scalability limits of traditional dynamic programming.
Jakob Foerster#139Mean Field Games provide a framework for modelling large populations. ICML26 Spotlight: Introducing Recurrent Structural Policy Gradient for partially observable MFGs with common noise, benefitting from faster convergence than model-free RL, but remaining tractable, unlike DP.
Users in the replies praise the Recurrent Structural Policy Gradient method for Mean Field Games because of its clear explanation, publicly available code, and linked paper.
