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Sinopsis
This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the “emergence” concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of “emergence” and to explain the feasibility of AI. To this end, it focuses on human perceptions of “utility.” It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.
The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as “novelty search” for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc.
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Acerca del autor
Hitoshi Iba received a PhD from the University of Tokyo, Japan, in 1990. From 1990 to 1998, he was with the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He is currently a Professor at the Department of Information and Communication Engineering, Graduate School of Information Science and Technology, the University of Tokyo. He has (co-)authored more than 200 papers and authored more than 40 books in English, Japanese, and Chinese. He is also an underwater naturalist and experienced PADI divemaster having completed more than a thousand dives.
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Deep Swarm and Evolution for Generative Artificial Intelligence (Paperback)
Publicado por
Taylor & Francis Ltd, London, 2026
ISBN 10: 1032828072
ISBN 13: 9781032828077
Nuevo
Paperback
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the emergence concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of emergence and to explain the feasibility of AI. To this end, it focuses on human perceptions of utility. It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as novelty search for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc. The book provides theoretical and practical knowledge about swarm and evolutionary approach, i.e. deep swarm and deep evolution, to generative AI and LLMs. It discusses the cognitive differences and similarities between humans and LLMs and describes intelligent behaviour of living organisms. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9781032828077
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Deep Swarm and Evolution for Generative Artificial Intelligence
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Deep Swarm and Evolution for Generative Artificial Intelligence (Paperback)
Publicado por
Taylor & Francis Ltd, London, 2026
ISBN 10: 1032828072
ISBN 13: 9781032828077
Nuevo
Paperback
Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Paperback. Condición: new. Paperback. This book provides theoretical and practical knowledge about swarm and evolutionary approach of generative AI and Large Language Models (LLMs). The development of such tools contributes to better optimizing methodologies with the integration of several machinelearning and deep learning techniques. In particular, it discusses how the emergence concept can contribute to the improvement of AI.The book aims to model human cognitive f unction in terms of emergence and to explain the feasibility of AI. To this end, it focuses on human perceptions of utility. It describes the emergence of various cognitive errors, and irrational behaviours in the multiobjective situations. It also reviews the cognitive differences and similarities between humans and LLMs. Such studies are important when applying LLMs to real-world tasks that involve human cognition, e.g., financial engineering and market issues.The book describes the intelligent behaviour of living organisms. This is to clarify how to achieve AI in the direction of artificial life. It describes sexual selection, which is a well-known natural phenomenon that troubled Darwin, i.e., why evolutionarily useless items evolved such as peacock feathers and moose antlers etc. The book shows how sexual selection is extended as novelty search for the application of generative AI, i.e., the image generation with diffusion model. Real-world applications are emphasised. Empirical examples from real-world data show how the concept of deep swarm and evolution is successfully applied when addressing tasks from such recent fields as robotics, e-commerce Web Shop and image generation etc. The book provides theoretical and practical knowledge about swarm and evolutionary approach, i.e. deep swarm and deep evolution, to generative AI and LLMs. It discusses the cognitive differences and similarities between humans and LLMs and describes intelligent behaviour of living organisms. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781032828077
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