Adaptive control [19, 112] is also concerned with
algorithms for improving a sequence of decisions from
experience. Adaptive control is a much more mature discipline that
concerns itself with dynamic systems in which states and actions are
vectors and system dynamics are smooth: linear or locally
linearizable around a desired trajectory. A very common formulation of
cost functions in adaptive control are quadratic penalties on
deviation from desired state and action vectors. Most importantly,
although the dynamic model of the system is not known in advance, and
must be estimated from data, the *structure* of the dynamic model
is fixed, leaving model estimation as a parameter estimation
problem. These assumptions permit deep, elegant and powerful
mathematical analysis, which in turn lead to robust, practical, and
widely deployed adaptive control algorithms.

Wed May 1 13:19:13 EDT 1996