ABB  Vol.5 No.4 , March 2014
Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements
ABSTRACT

Based on the biological key-lock-principle common in various biological systems such as the human brain, this paper relates to a method and device for creating problem-solving complexes from individual elements that can be coupled with one another and that have different properties to solve problems. The problem solution can be carried out either serially with a large computer, or with several independent, hierarchically joined computers. In this system, an independent control unit that assumes a multitude of tasks and also acts as an interface with access to all participating computers, is assigned to each problem or object class according to the amount of potential problem-oriented solutions. Such a unit prepares the partial solutions found in its computer for the totality of the solutions computed in the associated computers, finally leading to a total problem solution.


Cite this paper
Mitterauer, B. (2014) Method and Apparatus for Creating Problem-Solving Complexes from Individual Elements. Advances in Bioscience and Biotechnology, 5, 311-315. doi: 10.4236/abb.2014.54038.
References
[1]   Behr, J.P. (1994) The Lock-and-Key Principle, the State of the Art-100 Years on. John Wiley and Sons, West Sussex.

[2]   Mitterauer, B. (1989) Architektonik. Entwurf einer Metaphysik der Machbarkeit. Brandstätter, Wien.

[3]   Conrad, M. (1992) Molecular Computing: The Lock-Key Paradigm. Computer, 25, 11-20.
http://dx.doi.org/10.1109/2.166400

[4]   Berkholz, D.S., Shapovalov, M.V., Dunbrack, R.L. and Karplus, P.A. (2009) Conformation Dependence of Backbone Geometry in Proteins. Structure, 17, 1316-1325.

[5]   Adleman, L.M. (1998) Computing with DNA. Scientific American, 276, 54-61.
http://dx.doi.org/10.1038/scientificamerican0898-54

[6]   Mitterauer, B. (2007) Where and How Could Intentional Programs Be Generated in the Brain? A Hypothetical Model Based on Glial-Neuronal Interactions. BioSystems, 88, 101-112. http://dx.doi.org/10.1016/j.biosystems.2006.04.003

[7]   Koza, J.R. (1992) Non-Linear Genetic Algorithms for Solving Problems by Finding a Fit Composition of Functions. US Patent 5, 136, 686.

[8]   Kauffman, St.A. (1993) The Origins of Order. Self-Organization and Selection in Evolution. Oxford University Press, Oxford.

[9]   Mitterauer, B. (2004) Computer System, Particularly for Simulation of Human Perception via Sense Organs. United States Patent 6, 697, 789B2.

[10]   Raff, M.C., Barres, B.A., Burne, J.F., Coles, H.S., Ishizaki, Y. and Jacobson, M.D. (1993) Programmed Cell Death and the Control of Cell Survival: Lessons from the Nervous System. Science, 262, 695-700.
http://dx.doi.org/10.1126/science.8235590

[11]   Mitterauer, B. (2000) Verfahren und Einrichtung zur Bildung von Problemkomplexen aus Einzelnen Elementen Sowie Deren Verwendung. German Patentschrift, DE19844652C1.

[12]   Taherdangkoo, M., Paziresk, M, Yazdi, M. and Bagheri, M.H. (2012) An Efficient Algorithm for Function Optimization: Modified Stem Cells Algorithm. Central European Journal of Engineering, 3, 36-50.
http://dx.doi.org/10.2478/s13531-012-0047-8

[13]   Mitterauer, B. (2000) Some Principles for Conscious Robots. Journal of Intelligent Systems, 10, 27-56.
http://dx.doi.org/10.1515/JISYS.2000.10.1.27

 
 
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