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Computer Science - Theoretical Computer Science | Handbook of Natural Computing

Handbook of Natural Computing

Rozenberg, Grzegorz, Bäck, Thomas, Kok, Joost N. (Eds.)

4 volumes, not available separately

2012, LII, 2052 p. In 4 volumes, not available separately.

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  • We are now witnessing an exciting interaction between computer science and the natural sciences. Natural Computing is an important catalyst for this interaction, and this handbook is a major record of this important development.

Natural Computing is the field of research that investigates both human-designed computing inspired by nature and computing taking place in nature, i.e., it investigates models and computational techniques inspired by nature and also it investigates phenomena taking place in nature in terms of information processing.

Examples of the first strand of research covered by the handbook include neural computation inspired by the functioning of the brain; evolutionary computation inspired by Darwinian evolution of species; cellular automata inspired by intercellular communication; swarm intelligence inspired by the behavior of groups of organisms; artificial immune systems inspired by the natural immune system; artificial life systems inspired by the properties of natural life in general; membrane computing inspired by the compartmentalized ways in which cells process information; and amorphous computing inspired by morphogenesis. Other examples of natural-computing paradigms are molecular computing and quantum computing, where the goal is to replace traditional electronic hardware, e.g., by bioware in molecular computing. In molecular computing, data are encoded as biomolecules and then molecular biology tools are used to transform the data, thus performing computations. In quantum computing, one exploits quantum-mechanical phenomena to perform computations and secure communications more efficiently than classical physics and, hence, traditional hardware allows.

The second strand of research covered by the handbook, computation taking place in nature, is represented by investigations into, among others, the computational nature of self-assembly, which lies at the core of nanoscience, the computational nature of developmental processes, the computational nature of biochemical reactions, the computational nature of bacterial communication, the computational nature of brain processes, and the systems biology approach to bionetworks where cellular processes are treated in terms of communication and interaction, and, hence, in terms of computation.

We are now witnessing exciting interaction between computer science and the natural sciences. While the natural sciences are rapidly absorbing notions, techniques and methodologies intrinsic to information processing, computer science is adapting and extending its traditional notion of computation, and computational techniques, to account for computation taking place in nature around us. Natural Computing is an important catalyst for this two-way interaction, and this handbook is a major record of this important development.

Content Level » Research

Keywords » Amorphous computing - Ant colony optimization - Artificial chemistry - Artificial immune systems (AIS) - Biocomputing - Biologically inspired algorithms - Biologically inspired computing - Biomolecular computing - Cellular automata - Coevolution - Collision-based computing - Computational system biology - DNA computing - Darwinian evolution - Developmental computing - Emergent computation - Evolvable hardware - Feedforward networks - Gene assembly - Gene regulatory network - Genetics-based machine learning - Genomic computer - Independent component analysis (ICA) - Kernel methods - Membrane computing - Memetic algorithms - Molecular computation - Molecular computing - Morphogenesis - Multiobjective optimization - Nanocomputing - Natural computation - Natural computing - Neural networks - Pattern recognition - Process algebra - Quantum algorithms - Quantum complexity theory - Quantum computation - Quantum computing - Quantum cryptography - Quantum error correction - Quantum information theory - Quantum mechanics - Rough-fuzzy computing - Self-organizing maps (SOMs) - Simulated annealing - Social computing - Support vector machines (SVMs) - Swarm intelligence

Related subjects » Applied & Technical Physics - Artificial Intelligence - Computational Intelligence and Complexity - Nanotechnology - Theoretical Computer Science

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