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Viewing report
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Information Elicitation for Improving Optimization. Edition No. 1
VDM Publishing House, Aug 2008, Pages: 104
When we work on a practical scheduling task, we
usually do not have complete knowledge of the
related resources and constraints. For example, when
scheduling a conference, we may not know the exact
sizes of available rooms or equipment needs of some
speakers. The task of constructing a schedule based
on incomplete data gives rise to several related
problems, including the representation of
uncertainty, efficient search for schedules, and
elicitation of additional data that help to reduce
uncertainty. In this work we introduce a new
information elicitation approach aiming to resolve
uncertainty in order to increase quality of
optimization while keeping the number of questions
the user has to answer to a minimum. The approach
differs from other approaches in terms of working
with a continuous domain with a large number of
uncertain variables, not having a need for
bootstrapping, tight integration with the
optimization process and integration of multiple
approaches to elicitation.
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