Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
Deliberation scheduling for problem solving in time-constrained environments
Artificial Intelligence
Automatically generating abstractions for planning
Artificial Intelligence
Proceedings of the 1994 International Conference on Parallel and Distributed Systems
Knowledge-based anytime computation
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Optimizing decision quality with contract algorithms
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Monitoring the progress of anytime problem-solving
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
An Intelligent System Combining Different Resource-Bounded Reasoning Techniques
Applied Intelligence
Dynamic Composition of Information Retrieval Techniques
Journal of Intelligent Information Systems
Reactive control of dynamic progressive processing
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Adaptive control of acyclic progressive processing task structures
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 1
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Progressive processing is a resource-bounded reasoning technique that allows a system to incrementally construct a solution to a problem using a hierarchy of processing levels. This paper focuses on the problem of meta-level control of progressive processing in domains characterized by rapid change and high level of duration uncertainty. We show that progressive processing facilitates efficient run-time monitoring and meta-level control. Our solution is based on an incremental scheduler that can handle duration uncertainty by dynamically revising the schedule during execution time based on run-time information. We also show that a probabilistic representation of duration uncertainty reduces the frequency of schedule revisions and thus improves the performance of the system. Finally, an experimental evaluation shows the contributions of this approach and its suitability for a data transmission application.