A linear programming methodology for approximate dynamic programming - Díaz, Henry; Sala, Antonio; Armesto, Leopoldo (Zielona Góra: Uniwersytet Zielonogórski)
The linear programming (LP) approach to solve the Bellman equation in dynamic programming is a well-known option for finite state and input spaces to obtain an exact solution. However, with function approximation or continuous state spaces, refinements are necessary. This paper presents a methodology to make approximate dynamic programming via LP work in practical control applications with continuous state and input spaces. There are some guidelines on data and regressor choices needed to obtain meaningful and well-conditioned value function estimates.
Keywords: linear programming; approximate dynamic programming; control applications; neural networks