The connection between the maximum principle and dynamic programming in stochastic control
Xun Yu Zhouf
Abstract
Xun Yu Zhouf
Abstract
There are usually two ways to study optimal stochastic control problems: Pontryagin's maximum principle and Bellman's dynamic programming, involving an adjoint process ψ and the value function V, respectively. The classical result on the connection between the maximum principle and dynamic programming is known as ψ(t)=V x(t,◯(t)) where ◯(∣) is the optimal path. In this paper we establish a nonsmooth version of the classical result by employing the notions of super_ and sub_differential introduced by Crandall and Lions. Thus the illusory assumption that V is differentiate is dispensed with.
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There are usually two ways to study optimal stochastic control problems: Pontryagin's maximum principle and Bellman's dynamic programming, involving an adjoint process ψ and the value function V, respectively. The classical result on the connection between the maximum principle and dynamic programming is known as ψ(t)=V x(t,◯(t)) where ◯(∣) is the optimal path. In this paper we establish a nonsmooth version of the classical result by employing the notions of super_ and sub_differential introduced by Crandall and Lions. Thus the illusory assumption that V is differentiate is dispensed with.
Key concepts: Maximum principle, Mathematics, Dynamic programming, Bellman equation, Optimal control, Connection (principal bundle), Pontryagin's minimum principle, Path (computing)