  Recently path integral methods have been developed for stochastic optimal
control for a wide class of models with non-linear dynamics in continuous
space-time. Path integral methods find the control that minimizes the expected
cost-to-go. In this paper we show that under the same assumptions, path
integral methods generalize directly to risk sensitive stochastic optimal
control. Here the method minimizes in expectation an exponentially weighted
cost-to-go. Depending on the exponential weight, risk seeking or risk averse
behaviour is obtained. We demonstrate the approach on risk sensitive stochastic
optimal control problems beyond the linear-quadratic case, showing the
intricate interaction of multi-modal control with risk sensitivity.
