  We study optimal control problems governed by abstract infinite dimensional
stochastic differential equations using the dynamic programming approach. In
the first part, we prove Lipschitz continuity, semiconcavity and semiconvexity
of the value function under several sets of assumptions, and thus derive its
$C^{1,1}$ regularity in the space variable. Based on this regularity result, we
construct optimal feedback controls using the notion of the $B$-continuous
viscosity solutions for the associated Hamilton--Jacobi--Bellman equation. This
is done in the case when the noise coefficient is independent of the control
variable. We also discuss applications of our results to optimal control
problems for controlled stochastic reaction-diffusion equations and, under
economic motivations, to stochastic delay differential equations.
