A deliberative scheduling technique for a real-time agent architecture

In this paper, we present a heuristic to schedule complex task models (tasks that use Artificial Intelligence methods). These tasks are used in a real-time agent architecture called ARTIS. This architecture has been designed to build intelligent agents that work in hard real-time environments. To do this, the architecture provides scheduling at two levels. The first level assures the fulfilment of the hard temporal requirements, and the second level obtains a result of higher quality. The new heuristic, Slack-Slide Scheduling (SSS), works at the second level. It manages two types of methods: progressive refinement methods and multiple methods. The Slack-Slide Scheduling also attempts to reuse previous results in order to make better use of the existing CPU time while the first-level scheduler fulfils the deadlines.