A Stochastic Maximum Principle for Markov Chains of Mean-Field Type
Salah Eddine Choutri () and
Tembine Hamidou ()
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Salah Eddine Choutri: Department of Mathematics, KTH Royal Institute of Technology, 100 44 Stockholm, Sweden
Tembine Hamidou: Learning and Game Theory Laboratory, New York University Abu Dhabi, P.O. Box 129188, Abu Dhabi, UAE
Games, 2018, vol. 9, issue 4, 1-21
We derive sufficient and necessary optimality conditions in terms of a stochastic maximum principle (SMP) for controls associated with cost functionals of mean-field type, under dynamics driven by a class of Markov chains of mean-field type which are pure jump processes obtained as solutions of a well-posed martingale problem. As an illustration, we apply the result to generic examples of control problems as well as some applications.
Keywords: mean-field; nonlinear Markov chain; backward SDEs; optimal control; stochastic maximum principle (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jgames:v:9:y:2018:i:4:p:84-:d:177231
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