Real-Time Control of Approximate Processing
Keith Decker, Alan Garvey, Marty Humphrey, Victor Lesser · 1991
Approximate processing is an approach to real-time AI problem solving in domains in which compromise is possible between the resources required to generate a solution and the quality of that solution. It is a satisficing approach in which the goal is to produce accept- able solutions how to integrate approximate processing with the blackboard architecture[17]. However, in order to solve real-time problems with hard deadlines using a blackboard system, we need to have: (1) a predictable blackboard execution loop, (2) a representation of the set of current and future tasks and their estimated durations, and (3) a model of how to modify those tasks when their deadlines are projected to be missed, and how the modifications will affect the task durations and results. This paper describes four components for achieving these goals in an approximate process- ing blackboard system. A parameterized low-level control loop allows predictable knowledge source execution, multiple execution channels allow dynamic control over the computation involved in each task, a meta-controller allows a representation of the set of current and future tasks and their estimated durations and results, and a real-time blackboard scheduler monitors and modifies tasks during execution so that deadlines are met. An example is given that illustrates how these components work together to construct a satisficing solution to a time-constrained problem in the Distributed Vehicle Monitoring Testbed (DVMT). A brief sketch is given of the implementation of the system.