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      Evolutionary Daisyworld models: A new approach to studying complex adaptive systems

        , , , ,
      Ecological Informatics
      Elsevier BV

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          Statistical physics of social dynamics

          Statistical physics has proven to be a very fruitful framework to describe phenomena outside the realm of traditional physics. The last years have witnessed the attempt by physicists to study collective phenomena emerging from the interactions of individuals as elementary units in social structures. Here we review the state of the art by focusing on a wide list of topics ranging from opinion, cultural and language dynamics to crowd behavior, hierarchy formation, human dynamics, social spreading. We highlight the connections between these problems and other, more traditional, topics of statistical physics. We also emphasize the comparison of model results with empirical data from social systems.
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            Punctuated equilibrium and criticality in a simple model of evolution

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              Genetic algorithms: principles of natural selection applied to computation.

              A genetic algorithm is a form of evolution that occurs on a computer. Genetic algorithms are a search method that can be used for both solving problems and modeling evolutionary systems. With various mapping techniques and an appropriate measure of fitness, a genetic algorithm can be tailored to evolve a solution for many types of problems, including optimization of a function of determination of the proper order of a sequence. Mathematical analysis has begun to explain how genetic algorithms work and how best to use them. Recently, genetic algorithms have been used to model several natural evolutionary systems, including immune systems.
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                Author and article information

                Journal
                Ecological Informatics
                Ecological Informatics
                Elsevier BV
                15749541
                July 2010
                July 2010
                : 5
                : 4
                : 231-240
                Article
                10.1016/j.ecoinf.2010.03.003
                5e962d4f-570e-43f4-98da-17684998cabd
                © 2010

                http://www.elsevier.com/tdm/userlicense/1.0/

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