An actor-critic framework built on a time-inhomogeneous little q-function and conditional normalizing flows serves as a mesh-free solver for entropy-regularized jump-diffusion control problems and stochastic games.
Reinforcement learning in continuous time and space.Neural Computation, 12(1):219–245, 2000
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
math.OC 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
An Actor-Critic Framework for Continuous-Time Jump-Diffusion Controls with Normalizing Flows
An actor-critic framework built on a time-inhomogeneous little q-function and conditional normalizing flows serves as a mesh-free solver for entropy-regularized jump-diffusion control problems and stochastic games.