Choosing the cost vector of the linear programming approach to approximate dynamic programming
Daniela Pucci de Farias, Théophane Weber · 2008
We consider the linear programming approach to approximate dynamic programming. In the general case of linear combination of features, we prove the existence of a solution which can be used to generate a policy with performance proportional to the strength of the architecture. In the special case of features defined on a partition of the state space, we give a simpler method to find the solution, as well as a stronger performance bound.