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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Paperback. Condition: 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. Seller Inventory # 9786209257704
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Taschenbuch. Condition: 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. Seller Inventory # 9786209257704
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Paperback. Condition: 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 Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Seller Inventory # 9786209257704
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Paperback. Condition: 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. Seller Inventory # 9786209257704
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Taschenbuch. Condition: 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. Seller Inventory # 134487847
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Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. 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.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 212 pp. Englisch. Seller Inventory # 9786209257704
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Taschenbuch. Condition: 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. Seller Inventory # 9786209257704