Controlled Markov Processes and Viscosity SolutionsThis book is intended as an introduction to optimal stochastic control for continuous time Markov processes and to the theory of viscosity solutions. |
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Page 64
... definition , in most ap- plications an equivalent definition is obtained by replacing D with C ( Q ) . Indeed this is always the case when Gt is a partial differential operator . See Theorem 6.1 below . However , if Σ is not compact and ...
... definition , in most ap- plications an equivalent definition is obtained by replacing D with C ( Q ) . Indeed this is always the case when Gt is a partial differential operator . See Theorem 6.1 below . However , if Σ is not compact and ...
Page 72
... Definition 4.1 with either choice of D and Definition 4.2 are equivalent for any partial differen- tial equation with maximum principle . From the above proof it is also clear that in Definition 4.2 we could use test functions from any ...
... Definition 4.1 with either choice of D and Definition 4.2 are equivalent for any partial differen- tial equation with maximum principle . From the above proof it is also clear that in Definition 4.2 we could use test functions from any ...
Page 100
... definition of viscosity sub- and supersolutions of ( 11.2 ) in O. This definition is obtained by simply substituting the form ( 11.1 ) into Definition 4.2 . The following definition does not require H to satisfy ( 11.3 ) . Definition ...
... definition of viscosity sub- and supersolutions of ( 11.2 ) in O. This definition is obtained by simply substituting the form ( 11.1 ) into Definition 4.2 . The following definition does not require H to satisfy ( 11.3 ) . Definition ...
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Controlled Markov Processes and Viscosity Solutions Wendell H. Fleming,Halil Mete Soner Limited preview - 2006 |
Controlled Markov Processes and Viscosity Solutions Wendell H. Fleming,Halil Mete Soner No preview available - 2006 |
Common terms and phrases
admissible control assume assumptions boundary condition boundary data bounded c₁ Cą(Q calculus of variations Chapter classical solution consider constant continuous on Q convergence convex Corollary cylindrical region defined definition denote dynamic programming equation dynamic programming principle Dynkin formula Example exists exit finite first-order formulation Hamilton-Jacobi equation Hence HJB equation holds implies inequality initial data lateral boundary Lemma lim sup linear Lipschitz continuous Markov chain Markov control policy Markov processes maximum principle minimizing Moreover nonlinear obtain optimal control optimal control problem partial derivatives partial differential equation proof of Theorem prove result satisfies second-order Section semigroup stochastic differential equation Suppose t₁ test function Theorem 5.1 uniformly continuous unique value function variations problem Verification Theorem viscosity solution viscosity subsolution viscosity supersolution yields