2 papers
cs.LG2026
A Schrödinger Eigenfunction Method for Long-Horizon Stochastic Optimal Control
Louis Claeys, Artur Goldman, Zebang Shen +1
High-dimensional stochastic optimal control (SOC) becomes harder with longer planning horizons: existing methods scale linearly in the horizon , with performance often deteriora…
cs.GT2024
When is Mean-Field Reinforcement Learning Tractable and Relevant?
Batuhan Yardim, Artur Goldman, Niao He
Mean-field reinforcement learning has become a popular theoretical framework for efficiently approximating large-scale multi-agent reinforcement learning (MARL) problems exhibiting…