Open AccessFiltering method for linear and non-linear stochastic optimal control of partially observable systems II
Author(s) -
Ali Poursherafatan,
Ali Delavarkhalafi
Publication year - 2018
Publication title -
filomat
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.449
H-Index - 34
eISSN - 2406-0933
pISSN - 0354-5180
DOI - 10.2298/fil1814089p
Subject(s) - observable , mathematics , stochastic game , nonlinear system , state (computer science) , stochastic control , optimal control , mathematical optimization , function (biology) , control theory (sociology) , control (management) , algorithm , computer science , mathematical economics , artificial intelligence , physics , quantum mechanics , evolutionary biology , biology
In this paper we studied stochastic optimal control problem based on partially observable systems (SOCPP) with a control factor on the diffusion term. A SOCPP has state and observation processes. This kind of problem has also a minimum payoff function. The payoff function should be minimized according to the partially observable systems consist of the state and observation processes. In this regard, the filtering method is used to evaluat this kind of problem and express full consideration of it. Finally, presented estimation methods are used to simulate the solution of a partially observable system corresponding to the control factor of this problem. These methods are numerically used to solve linear and nonlinear cases.