An algorithm for finding reliably schedulable plans

Bálint Takács, István Szita, András Lõrincz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

For interacting agents in time-critical applications, learning whether a subtask can be scheduled reliably is an important issue. The identification of sub-problems of this nature may promote e.g. planning, scheduling and segmenting in Markov decision processes. We define a subtask to be schedulable if its execution time has a small variance. We present an algorithm for finding such subtasks.

Original languageEnglish
Title of host publication2004 IEEE International Joint Conference on Neural Networks - Proceedings
Pages2257-2261
Number of pages5
DOIs
Publication statusPublished - Dec 1 2004
Event2004 IEEE International Joint Conference on Neural Networks - Proceedings - Budapest, Hungary
Duration: Jul 25 2004Jul 29 2004

Publication series

NameIEEE International Conference on Neural Networks - Conference Proceedings
Volume3
ISSN (Print)1098-7576

Other

Other2004 IEEE International Joint Conference on Neural Networks - Proceedings
CountryHungary
CityBudapest
Period7/25/047/29/04

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ASJC Scopus subject areas

  • Software

Cite this

Takács, B., Szita, I., & Lõrincz, A. (2004). An algorithm for finding reliably schedulable plans. In 2004 IEEE International Joint Conference on Neural Networks - Proceedings (pp. 2257-2261). (IEEE International Conference on Neural Networks - Conference Proceedings; Vol. 3). https://doi.org/10.1109/IJCNN.2004.1380973