1. A method for providing decision-making support under uncertainty in a multi-level business process, wherein process events can be stochastic events, the method comprising: deploying an adaptive stochastic control algorithm for generating actions in response to process situations; assembling expert knowledge of process situations, actions and outcomes corresponding to each level of the multi-level business process; using the expert knowledge as a unified representation of the business process; and using a process model in conjunction with the unified representation of the business process for reinforcement learning so that the stochastic adaptive control algorithm is trained to generate optimal actions.