Scheduling with Uncertain Resources: Learning to Make Reasonable AssumptionsProceedings of the IEEE International Conference on Systems, Man, and Cybernetics
Date of Original Version10-1-2008
Abstract or DescriptionWe consider the task of scheduling a conference based on incomplete information about resources and constraints, and describe a mechanism for the dynamic learning of related default assumptions, which enable the scheduling system to make reasonable guesses about missing data. We outline the representation of incomplete knowledge, describe the learning procedure, and demonstrate that the learned knowledge improves the scheduling results.
Citation InformationSteven Gardiner, Eugene Fink and Jaime G. Carbonell. "Scheduling with Uncertain Resources: Learning to Make Reasonable Assumptions" Proceedings of the IEEE International Conference on Systems, Man, and Cybernetics (2008) p. 2554 - 2559
Available at: http://works.bepress.com/jaime_carbonell/73/