We present a novel linear program for the approximation of the dynamic programming cost-to-go function in high-dimensional stochastic control problems. LP approaches to approximate DP have typically ...

This is a preview. Log in through your library . Abstract The paper solves the stochastic inverse optimal problem. Dynamic programming is used to transform the original problem into a differential ...

This course covers reinforcement learning aka dynamic programming, which is a modeling principle capturing dynamic environments and stochastic nature of events. The main goal is to learn dynamic ...

Alongside its Gemini generative AI model, Google this morning took the wraps off of AlphaCode 2, an improved version of the code-generating AlphaCode introduced by Google’s DeepMind lab roughly a year ...

This paper proposes a new deep-learning-based algorithm for high-dimensional Bermudan option pricing. To the best of our knowledge, this is the first study of the arbitrary-order discretization scheme ...