02762cam a22003495a 4500001001400000003000400014005001700018008004100035020001800076040002600094082001900120100002900139245007200168250001200240260003700252300003400289490004200323500002400365504003100389505062600420506006201046520093201108650004402040650006202084651001002146653002202156700001702178710003402195942000802229999001702237952015802254ssj0001558339OSt20160424131140.0150701t2015    gw a   frb    001 0 eng d  a9783662448731  dWaSeSSdEG-ScBUEbeng04a006.3222bEIB1 aEiben, Agoston E.93988910aIntroduction to evolutionary computing /cA. E. Eiben, J. E. Smith.  a2nd ed.  aHeidelberg :bSpringer,cc.2015.  axii, 287 p. :bill. ;c24 cm.0 aNatural Computing Series,x1619-7127.  aIndex : p. 283-287.  aBibliography : p. 259-282.0 aProblems to Be Solved -- Evolutionary Computing: The Origins -- What Is an Evolutionary Algorithm? -- Representation, Mutation, and Recombination -- Fitness, Selection, and Population Management -- Popular Evolutionary Algorithm Variants -- Hybridisation with Other Techniques: Memetic Algorithms -- Nonstationary and Noisy Function Optimisation -- Multiobjective Evolutionary Algorithms -- Constraint Handling -- Interactive Evolutionary Algorithms -- Coevolutionary Systems -- Theory -- Evolutionary Robotics -- Parameters and Parameter Tuning -- Parameter Control -- Working with Evolutionary Algorithms -- References.  aAvailable on campus and off campus with authorized login.  aThe overall structure of this new edition is three-tier: Part I presents the basics, Part II is concerned with methodological issues, and Part III discusses advanced topics. In the second edition the authors have reorganized the material to focus on problems, how to represent them, and then how to choose and design algorithms for different representations. They also added a chapter on problems, reflecting the overall book focus on problem-solvers, a chapter on parameter tuning, which they combined with the parameter control and "how-to" chapters into a methodological part, and finally a chapter on evolutionary robotics with an outlook on possible exciting developments in this field. The book is suitable for undergraduate and graduate courses in artificial intelligence and computational intelligence, and for self-study by practitioners and researchers engaged with all aspects of bioinspired design and optimization. 7aEvolutionary computation.9398902BUEsh 7aEvolutionary programming (Computer science)9398912BUEsh  2BUEsh  bCOMSCIcApril20161 aSmith, J. E.2 aSpringerLink (Online service)  2ddc  c21675d21647  00102ddc40708AlahramaMAINbMAINcLOWd2016-04-24ePurchaseg399.00l1o006.3 EIBp000032402q2024-03-09r2024-02-07 00:00:00s2024-02-07v498.75yBB