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'''Natural computation''', also called '''natural computing''', can be defined as the field of research that, based on or inspired by [[nature]], allows the development of new computational tools (in software, hardware or ‘wetware’) for problem solving, leads to the synthesis of natural patterns, behaviors and organisms, and may result in the design of novel computing systems that use natural media to compute. Natural computing can be divided into three main branches: |
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1) Computing inspired by nature (also called [[Biologically inspired computing]]): it makes use of nature as inspiration for the development of problem solving techniques. The main idea of this branch is to develop computational tools (algorithms) by taking inspiration from nature for the solution of complex problems; |
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2) The simulation and emulation of nature by means of computing: it is basically a synthetic process aimed at creating patterns, forms, behaviors, and organisms that (do not necessarily) resemble ‘life-as-we-know-it’. Its products can be used to mimic various natural phenomena, thus increasing our understanding of nature and insights about computer models; and |
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3) Computing with natural materials: it corresponds to the use of natural materials to perform computation, thus constituting a true novel computing paradigm that comes to substitute or supplement the current silicon-based computers. |
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The academic journal of record in this field is ''[[Natural Computing]]''. |
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== Benefits == |
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Benefits of natural computation technologies often mimic those found in real natural systems. These include: |
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* Flexibility |
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** NC techniques can often be applied to a very wide range of problems and with varying constraints. |
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* Adaptability |
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** NC algorithms are often good at dealing with unseen data and learning to handle it through intelligent acquisition of information. |
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* Robustness |
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** NC techniques are often very good at dealing with incomplete data, or data with anomalous features. |
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* Decentralised control |
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** Many NC techniques utilise a decentralised approach where there is no central hub coordinating computational activities. |
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== Techniques == |
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# Computing inspired by nature: |
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#* [[Evolutionary computation]] |
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#* [[Neural networks]] |
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#* [[Artificial immune systems]] |
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#* [[Swarm intelligence]] |
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# Simulation and emulation of nature by means of computing |
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#* [[Fractal geometry]] |
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#* [[Artificial life]] |
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# Computing with natural materials |
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#* [[Quantum computing]] |
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== Further reading == |
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* DE CASTRO, L. N. Natural Computing. In: Mehdi Khosrow-Pour. (Ed.). Encyclopedia of Information Sciences and Technology. Idea Group Reference, 2005, vol. IV, pp. 2080-2084. |
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* [http://lsin.unisantos.br/lnunes/books/natcomp.html DE CASTRO, L. N. Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications. Chapman & Hall/CRC, 2006] |
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There are several leading research centres in nature inspired computation. Some of those are listed below. |
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* [http://www.hpl.hp.com/research/bicas/ BICAS] HP Labs, Bristol UK |
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* [http://www.lcnc.nl/ Leiden Center for Natural Computation] Leiden, The Netherlands |
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* [http://www.cs.bham.ac.uk/research/labs/natural_computation/ Natural Computation Research] University of Birmingham, Birmingham UK |
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* [http://ncra.ucd.ie NCRA] UCD, Dublin Ireland |
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[[Category:Computer science]] |
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[[Category:Biology]] |
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[[Category:Mathematics]] |
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[[Category:Statistics]] |
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Latest revision as of 02:30, 13 April 2011
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