| Sumario: | A complex system is one that generates emergent structures, usually by the repeated application of relatively simple rules. The structures are emergent in the sense that they are not specified in, and cannot be predicted from, the rules that produce them. Mitchell argues for a unified science of complexity but does not ultimately succeed in providing a coherent account. Her book is nevertheless useful as an introduction to some systems and algorithms that have been studied in complexity research and that may be applicable to natural phenomena, including the behavior of organisms. The book also contains interesting historical and biographical details about complexity research and some of the mathematicians and scientists who have contributed to it. A sample of the specific complex systems and algorithms Mitchell introduces is examined in this review, including iterated maps, cellular automata, genetic algorithms, and small world and random Boolean networks. The relevance of complexity theory for behavior analysis is also considered, including applications of simple rules, networks, cellular automata, and genetic algorithms.
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