We address the problem of building an interruptible real-time system using non-interruptible components. Some artificial intelligence techniques offer a tradeoff between computation time and quality of results, but their run-time must be determined when they are activated. These techniques, called contract algorithms, introduce a complex scheduling problem when there is uncertainty about the amount of time available for problem-solving. We show how to optimally sequence contract algorithms to create the best possible interruptible system with or without stochastic information about the deadline. These results extend the foundation of real-time problem-solving and provide useful guidance for embedding contract algorithms in applications.