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Biological computation /

The area of biologically inspired computing, or biological computation, involves the development of new, biologically based techniques for solving difficult computational problems. A unified overview of computer science ideas inspired by biology, Biological Computation presents the most fundamental...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor principal: Lamm, Ehud
Otros Autores: Unger, Ron
Formato: Electrónico eBook
Idioma:Inglés
Publicado: [Place of publication not identified] : Chapman and Hall/CRC, 2011.
Colección:Chapman & Hall/CRC mathematical and computational biology series
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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520 3 |a The area of biologically inspired computing, or biological computation, involves the development of new, biologically based techniques for solving difficult computational problems. A unified overview of computer science ideas inspired by biology, Biological Computation presents the most fundamental and significant concepts in this area. In the book, students discover that bacteria communicate, that DNA can be used for performing computations, how evolution solves optimization problems, that the way ants organize their nests can be applied to solve clustering problems, and what the human immune system can teach us about protecting computer networks. The authors discuss more biological examples such as these, along with the computational techniques developed from these scenarios. 
505 0 |a Introduction and Biological Background; Biological Computation; The Influence of Biology on Mathematics--Historical Examples; Biological Introduction; Models and Simulations Cellular Automata ; Biological Background; The Game of Life; General Definition of Cellular Automata; One-Dimensional Automata; Examples of Cellular Automata; Comparison with a Continuous Mathematical Model; Computational Universality; Self-Replication; Pseudo Code Evolutionary Computation ; Evolutionary Biology and Evolutionary Computation; Genetic Algorithms; Example Applications; Analysis of the Behavior of Genetic Algorithms; Lamarckian Evolution; Genetic Programming; A Second Look at the Evolutionary Process; Pseudo Code Artificial Neural Networks ; Biological Background; Learning; Artificial Neural Networks; The Perceptron; Learning in a Multilayered Network; Associative Memory; Unsupervised Learning Molecular Computation; Biological Background; Computation Using DNA; Enzymatic Computation The Never-Ending Story: Additional Topics at the Interface between Biology and Computation ; Swarm Intelligence; Artificial Immune Systems; Artificial Life; Systems Biology; Recommendations for Additional Reading A Summary, Further Reading, Exercises, and Answers appear at the end of each chapter. 
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