  This paper explores the use of laboratory closed-loop learning control to
either fight or cooperate with decoherence in the optimal manipulation of
quantum dynamics. Simulations of the processes are performed in a Lindblad
formulation on multilevel quantum systems strongly interacting with the
environment without spontaneous emission. When seeking a high control yield it
is possible to find fields that successfully fight with decoherence while
attaining a good quality yield. When seeking modest control yields, fields can
be found which are optimally shaped to cooperate with decoherence and thereby
drive the dynamics more efficiently. In the latter regime when the control
field and the decoherence strength are both weak, a theoretical foundation is
established to describe how they cooperate with each other. In general, the
results indicate that the population transfer objectives can be effectively met
by appropriately either fighting or cooperating with decoherence.
