Stuart Kauffman William G. Macready Emily Dickinson
Abstract
Optimization of systems with many conflicting constraints arises in numerous settings. Common optimization procedures seek to improve performance of the system as a whole. We show that coevolutionary problem solving, in which a system is partitioned into subsystems each of which selfishly optimizes, can lead to enhanced performance as a collective emergent property. Optimally partitioned systems often lie near a transistion from order to chaos.
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Paper provided by Santa Fe Institute in its series Working Papers with number
94-06-031.
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