LEADER 04496nam  22007695  450 
001 9910300556103321
005 20201222143324.0
010   $a3-319-70205-X
024 7 $a10.1007/978-3-319-70205-6
035   $a(CKB)4100000001795133
035   $a(DE-He213)978-3-319-70205-6
035   $a(MiAaPQ)EBC5219541
035   $a(PPN)223956783
035   $a(EXLCZ)994100000001795133
100   $a20180111d2018      u|         0
101 0 $aeng
135   $aurnn|008mamaa
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aStatistical Physics and Computational Methods for Evolutionary Game Theory /$fby Marco Alberto Javarone
205   $a1st ed. 2018.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018.
215   $a1 online resource (IX, 74 p. 27 illus., 25 illus. in color.) 
225 1 $aUnderstanding Complex Systems,$x2191-5326
311   $a3-319-70204-1 
320   $aIncludes bibliographical references at the end of each chapters.
327   $aChapter 1. Introduction -- Chapter 2. Modeling Complex Systems -- Chapter 3. Evolutionary Games I: Statistical Physics -- Chapter 4 Evolutionary Games II: Applications -- Chapter 5. Conclusions.
330   $aThis book presents an introduction to Evolutionary Game Theory (EGT) which is an emerging field in the area of complex systems attracting the attention of researchers from disparate scientific communities. EGT allows one to represent and study several complex phenomena, such as the emergence of cooperation in social systems, the role of conformity in shaping the equilibrium of a population, and the dynamics in biological and ecological systems. Since EGT models belong to the area of complex systems, statistical physics constitutes a fundamental ingredient for investigating their behavior. At the same time, the complexity of some EGT models, such as those realized by means of agent-based methods, often require the implementation of numerical simulations. Therefore, beyond providing an introduction to EGT, this book gives a brief overview of the main statistical physics tools (such as phase transitions and the Ising model) and computational strategies for simulating evolutionary games (such as Monte Carlo algorithms on lattices).  This book will appeal to students and researchers in this burgeoning field of complex systems.
410  0$aUnderstanding Complex Systems,$x2191-5326
606   $aStatistical physics
606   $aGame theory
606   $aSocial sciences?Data processing
606   $aSocial sciences?Computer programs
606   $aSociophysics
606   $aEconophysics
606   $aEvolution (Biology)
606   $aPython (Computer program language)
606   $aStatistical Physics and Dynamical Systems$3https://scigraph.springernature.com/ontologies/product-market-codes/P19090
606   $aGame Theory, Economics, Social and Behav. Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/M13011
606   $aComputational Social Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/X34000
606   $aData-driven Science, Modeling and Theory Building$3https://scigraph.springernature.com/ontologies/product-market-codes/P33030
606   $aEvolutionary Biology$3https://scigraph.springernature.com/ontologies/product-market-codes/L21001
606   $aPython$3https://scigraph.springernature.com/ontologies/product-market-codes/I29080
615  0$aStatistical physics.
615  0$aGame theory.
615  0$aSocial sciences?Data processing.
615  0$aSocial sciences?Computer programs.
615  0$aSociophysics.
615  0$aEconophysics.
615  0$aEvolution (Biology)
615  0$aPython (Computer program language)
615 14$aStatistical Physics and Dynamical Systems.
615 24$aGame Theory, Economics, Social and Behav. Sciences.
615 24$aComputational Social Sciences.
615 24$aData-driven Science, Modeling and Theory Building.
615 24$aEvolutionary Biology.
615 24$aPython.
676   $a530.13
700   $aJavarone$b Marco Alberto$4aut$4http://id.loc.gov/vocabulary/relators/aut$01064359
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910300556103321
996   $aStatistical Physics and Computational Methods for Evolutionary Game Theory$92537607
997   $aUNINA