A key component of a Joint Air Operation (JAO) environment is the planning and dynamic control of missions in the presence of uncertainties. This involves the assignment of resources (e.g., different aircraft types) to targets while taking into account and anticipating the effect of random future events and, subsequently, dynamic control in response to various controllable and uncontrollable events as missions are executed in a hostile and rapidly changing setting. The objective is to maximize the reward associated with targets while minimizing loss of resources. In this paper, we first formulate the problem of optimal mission assignment and identify the complexities involved due to combinatorial and stochastic characteristics. We then describe a discrete event simulation tool developed to model the JAO environment and all of its dynamics and stochastic elements and to provide a testbed for several methods we are developing to solve the problem of agile mission control. We describe some of these methods, including approximate dynamic programming using rollout algorithms and optimal resource allocation schemes, and present some numerical results.