A centralised hierarchical task scheduler for an urban traffic control system based on a multiagent architecture

In this paper we present a scheduler suitable to be applied to a particular class of dynamic systems, which main characteristics are the lack of actual data during long time periods and the unreliability on the available data. The management of these systems requires the integration of simulation techniques, temporal reasoning, soft real-time and mechanisms of reason maintenance. To deal with all of these qualities it is showed a centralized hierarchical task scheduler, which main operation characteristics are event oriented and hierarchical task oriented. We apply this scheduler to a deep knowledge expert system developed for monitoring and helping to the decision taking in an urban traffic control system.