The paper introduces an entropy-regularized RL framework deriving exploratory weakly-coupled HJBI equations and using neural networks to approximate value functions for high-dimensional LQ-SDGs under Markov regime switching.
Actor-critic method for high dimensional static hamilton–jacobi–bellman partial differential equations based on neural networks,
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Entropy-Regularized Reinforcement Learning for Linear-Quadratic Stackelberg Differential Games in Regime-Switching Diffusion Models
The paper introduces an entropy-regularized RL framework deriving exploratory weakly-coupled HJBI equations and using neural networks to approximate value functions for high-dimensional LQ-SDGs under Markov regime switching.