Algorithms and Data Structures
Reference documents in Algorithms and Data Structures.
Documents in Algorithms and Data Structures
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Bio-inspired computational algorithms are always hot research topics in artificial intelligence communities. Biology is a bewildering source of inspiration for the design of intelligent artifacts that are capable of efficient and autonomous operation in unknown and changing environments.
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This well-organized book takes the reader through the new and rapidly expanding field of Genetic Algorithms step by step, from a discussion of numerical optimization, to a survey of current extensions to genetic algorithms and applications.
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This book discusses algorithmic developments in the context of Genetic Algorithms (GAs) and Genetic Programming (GP). It applies the algorithms to significant combinatorial optimization problems and describes structure identification using HeuristicLab as a platform for algorithm development.
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The book describes 45 algorithms from the field of Artificial Intelligence. All algorithm descriptions are complete and consistent to ensure that they are accessible, usable and understandable by a wide audience.
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A comprehensive introduction to optimization with a focus on practical algorithms for the design of engineering systems.
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This book gives you experience making Genetic Algorithms (GAs) work for you, using easy-to-follow example projects that you can fall back upon when learning to use other machine learning tools and techniques.
