Continuous time Markov chain based approximations of stationary and weak KAM Hamilton-Jacobi equations
Continuous time Markov chain based approximations of stationary and weak KAM Hamilton-Jacobi equations
Аннотация:
The main objects of this paper are the stationary and weak KAM Hamilton-Jacobi equations on the finite-dimensional torus.
The key idea of the paper is to replace the underlying calculus of variations problems with continuous time Markov decision problems. This leads directly to an approximation of the stationary Hamilton-Jacobi equation by the Bellman equation for a discounted Markov decision problem. Developing elements of the weak KAM theory for the Markov decision problem, we obtain an approximation of the effective Hamiltonian. Additionally, convergences of the functional parts of the discrete weak KAM equations and Mather measures are shown. It turns out that the approximating equations are systems of algebraic equations. Thus, the paper's result can be seen as numerical schemes for stationary and weak KAM Hamilton-Jacobi equations.
Ключевые слова: Hamilton-Jacobi equation, discrete weak KAM theory, Markov chain approximation, discrete Mather measure
