Genetic AI explores how evolutionary principles shape digital intelligence. Part I traces the roots from Darwin to Turing, explaining how populations, fitness, and genotype–phenotype mappings form the conceptual core. Part II introduces the main algorithmic toolkit: Genetic Algorithms for combinatorial search, Evolution Strategies for continuous optimization, Genetic Programming for evolving code, and other paradigms including Evolutionary Programming, Differential Evolution, and multi-modal or multi-objective optimization. Part III focuses on practical applications such as neuroevolution for evolving neural networks, evolutionary robotics for adaptive embodied agents, developmental systems for generative complexity, interactive evolutionary computation driven by human preference, and quality-diversity methods enabling open-ended exploration. Part IV covers the theoretical foundations and large-scale implementations that support efficient evolutionary computation. Part V looks ahead to the future, addressing emerging capabilities and the ethical implications of self-evolving autonomous systems.
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Dr. J. MERCY GERALDINE, M.E., Ph.D., is Professor and Head of Computer Science and Engineering at Dhanalakshmi Srinivasan University, Trichy. Dr. H. KRISHNAVENI , MCA.,Mphil.,SET.,PhD., has 24 years of teaching and 8 years of research experience in the field of Computer Science.
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Paperback. Zustand: new. Paperback. Genetic AI explores how evolutionary principles shape digital intelligence. Part I traces the roots from Darwin to Turing, explaining how populations, fitness, and genotype-phenotype mappings form the conceptual core. Part II introduces the main algorithmic toolkit: Genetic Algorithms for combinatorial search, Evolution Strategies for continuous optimization, Genetic Programming for evolving code, and other paradigms including Evolutionary Programming, Differential Evolution, and multi-modal or multi-objective optimization. Part III focuses on practical applications such as neuroevolution for evolving neural networks, evolutionary robotics for adaptive embodied agents, developmental systems for generative complexity, interactive evolutionary computation driven by human preference, and quality-diversity methods enabling open-ended exploration. Part IV covers the theoretical foundations and large-scale implementations that support efficient evolutionary computation. Part V looks ahead to the future, addressing emerging capabilities and the ethical implications of self-evolving autonomous systems. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786209257704
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Taschenbuch. Zustand: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Genetic AI explores how evolutionary principles shape digital intelligence. Part I traces the roots from Darwin to Turing, explaining how populations, fitness, and genotype-phenotype mappings form the conceptual core. Part II introduces the main algorithmic toolkit: Genetic Algorithms for combinatorial search, Evolution Strategies for continuous optimization, Genetic Programming for evolving code, and other paradigms including Evolutionary Programming, Differential Evolution, and multi-modal or multi-objective optimization. Part III focuses on practical applications such as neuroevolution for evolving neural networks, evolutionary robotics for adaptive embodied agents, developmental systems for generative complexity, interactive evolutionary computation driven by human preference, and quality-diversity methods enabling open-ended exploration. Part IV covers the theoretical foundations and large-scale implementations that support efficient evolutionary computation. Part V looks ahead to the future, addressing emerging capabilities and the ethical implications of self-evolving autonomous systems. 212 pp. Englisch. Bestandsnummer des Verkäufers 9786209257704
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Taschenbuch. Zustand: Neu. Genetic AI | Algorithms, Theory, and Computational Evolution | J. Mercy Geraldine (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209257704 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 134487847
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Paperback. Zustand: new. Paperback. Genetic AI explores how evolutionary principles shape digital intelligence. Part I traces the roots from Darwin to Turing, explaining how populations, fitness, and genotype-phenotype mappings form the conceptual core. Part II introduces the main algorithmic toolkit: Genetic Algorithms for combinatorial search, Evolution Strategies for continuous optimization, Genetic Programming for evolving code, and other paradigms including Evolutionary Programming, Differential Evolution, and multi-modal or multi-objective optimization. Part III focuses on practical applications such as neuroevolution for evolving neural networks, evolutionary robotics for adaptive embodied agents, developmental systems for generative complexity, interactive evolutionary computation driven by human preference, and quality-diversity methods enabling open-ended exploration. Part IV covers the theoretical foundations and large-scale implementations that support efficient evolutionary computation. Part V looks ahead to the future, addressing emerging capabilities and the ethical implications of self-evolving autonomous systems. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209257704
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Taschenbuch. Zustand: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Genetic AI explores how evolutionary principles shape digital intelligence. Part I traces the roots from Darwin to Turing, explaining how populations, fitness, and genotype-phenotype mappings form the conceptual core. Part II introduces the main algorithmic toolkit: Genetic Algorithms for combinatorial search, Evolution Strategies for continuous optimization, Genetic Programming for evolving code, and other paradigms including Evolutionary Programming, Differential Evolution, and multi-modal or multi-objective optimization. Part III focuses on practical applications such as neuroevolution for evolving neural networks, evolutionary robotics for adaptive embodied agents, developmental systems for generative complexity, interactive evolutionary computation driven by human preference, and quality-diversity methods enabling open-ended exploration. Part IV covers the theoretical foundations and large-scale implementations that support efficient evolutionary computation. Part V looks ahead to the future, addressing emerging capabilities and the ethical implications of self-evolving autonomous systems. Bestandsnummer des Verkäufers 9786209257704
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