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Mean-field stochastic control with elephant memory in finite and infinite time horizon
Authors:Nacira Agram
Affiliation:1. Department of Mathematics, University of Oslo, Oslo, Norway;2. Department of Mathematics, Linnaeus University (LNU), V?xj?, Sweden
Abstract:ABSTRACT

Our purpose of this paper is to study stochastic control problems for systems driven by mean-field stochastic differential equations with elephant memory, in the sense that the system (like the elephants) never forgets its history. We study both the finite horizon case and the infinite time horizon case.
  • In the finite horizon case, results about existence and uniqueness of solutions of such a system are given. Moreover, we prove sufficient as well as necessary stochastic maximum principles for the optimal control of such systems. We apply our results to solve a mean-field linear quadratic control problem.

  • For infinite horizon, we derive sufficient and necessary maximum principles.

    As an illustration, we solve an optimal consumption problem from a cash flow modelled by an elephant memory mean-field system.

Keywords:Mean-field stochastic differential equation  memory  stochastic maximum principle  partial information  backward stochastic differential equation
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