Swarm Intelligence and Deep Evolution: Evolutionary Approach to Artificial Intelligence

· CRC Press
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288
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Bu e-kitob haqida

The book provides theoretical and practical knowledge about swarm intelligence and evolutionary computation. It describes the emerging trends in deep learning that involve the integration of swarm intelligence and evolutionary computation with deep learning, i.e., deep neuroevolution and deep swarms. The study reviews the research on network structures and hyperparameters in deep learning, and attracting attention as a new trend in AI. A part of the coverage of the book is based on the results of practical examples as well as various real-world applications. The future of AI, based on the ideas of swarm intelligence and evolution is also covered.

The book is an introductory work for researchers. Approaches to the realization of AI and the emergence of intelligence are explained, with emphasis on evolution and learning. It is designed for beginners who do not have any knowledge of algorithms or biology, and explains the basics of neural networks and deep learning in an easy-to-understand manner. As a practical exercise in neuroevolution, the book shows how to learn to drive a racing car and a helicopter using MindRender. MindRender is an AI educational software that allows the readers to create and play with VR programs, and provides a variety of examples so that the readers will be able to create and understand AI.

Muallif haqida

Hitoshi Iba is a Professor at the Graduate School of Information Science and Technology at the University of Tokyo. From 1990 to 1998, he was a senior researcher at the Electro Technical Laboratory (ETL) in Ibaraki, Japan. He is a founding associate editor of the Journal of Genetic Programming and Evolvable Machines (GPEM) and was a founding associate editor of IEEE transactions on Evolutionary Computation. He has published more than one hundred papers and is also a (co-)author of more than ten books. He is also an underwater naturalist and experienced PADI divemaster having completed more than a thousand dives.

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