Deriving reservoir operating policies using classifier systems

An application of classifier systems to time variant, water resources allocation problems is described, the aim of the work being to assess the suitability of the technique for deriving control strategies. The difficulties of allocating credit to classifiers where co-operating sequences of rules have to be developed are discussed and methods for overcoming some of the difficulties are covered. The training of the classifier on two problems, the first containing a single, surface water reservoir and the second two reservoirs is used to develop techniques and the results show that classifiers possess an ability to learn about the domain. However the resulting operating strategies are not appropriate for the operation of water resources systems. The work indicates that in their current format, classifier systems cannot learn to operate systems where long, interdependent chains of decisions are involved.

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