Entropy Reduction Engine Architecture Methodological Assumptions
The ERE (Entropy Reduction Engine) project focuses on problems that require
planning,
scheduling and
control. Traditional
AI research usually focuses on either
selection of actions (planning) or scheduling of actions with respect to time. The ERE
attempts to integrate both of these actions along with the
closed loop control of plan
execution, so that replanning can occur if difficulties arise.
In order to address this wide range of problems the ERE uses many different
problem
solving methods, including problem reduction, temporal projection, and rule based
execution. In addition, both
inductive and
analytical
learning methods are used.
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Methodological Assumptions
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