Computational inspiration

Occasionally, he has approached an experimentalist with a computationally inspired problem. In working with Bader s Atoms-In-Molecules theory, Grimme was interested in whether bond paths really correlate with bonds. Grimme proposed to Erker to synthesize 4,5-dideuterated phenanthrene and we got spectroscopists to measure this ... 

Computational inspiration is a process of using natural evolution and growth processes to develop similar computational processes that can be used in computer programs for the automated development of design concepts, including inventive design concepts. 

We will focus on two specific forms of computational inspiration that are particularly promising for inventive engineers. First, we will discuss evolutionary computation (EC), which is inspired by the mechanisms of the evolution of natural systems. Next, we will overview cellular automata, which are inspired by the mechanisms of growth in natural systems. 

My own experience with calculating machines is so limited that it would be difficult for me to deal with their use in any detail. This would also be unnecessary, since the use of computers will be discussed by Drs. Ehrlich, Varga, Richtmyer and Carlson along with the mathematical models, such as multigroup theories, which the availability of computers inspired. 

Experimental techniques based on the application of mechanical forces to single molecules in small assemblies have been applied to study the binding properties of biomolecules and their response to external mechanical manipulations. Among such techniques are atomic force microscopy (AFM), optical tweezers, biomembrane force probe, and surface force apparatus experiments (Binning et al., 1986 Block and Svoboda, 1994 Evans et ah, 1995 Israelachvili, 1992). These techniques have inspired us and others (see also the chapters by Eichinger et al. and by Hermans et al. in this volume) to adopt a similar approach for the study of biomolecules by means of computer simulations. 

The world of colloidal particles is large and fasdnating. Basic simulation techniques rapidly lead to challenging questions and new things to be discovered. Computer simulations are close enough to experiments to allow intellectual inspiration as well as a quantitative comparison of the results. We have reviewed the basic simulation techniques and their principal implementation but could only briefly mention advanced techniques and results. A survey of the recent literature shows the variety of physical effects present in colloidal systems and accessible to computer simulations. 

Thermal computation which comprises algorithms inspired by multiparticle systems like BROWNian motion (BROWNian search, Monte Carlo search) on the one hand and simulated annealing which is inspired by Boltzmanns statistics on the other hand. 

Evolutionary computation which is learned by watching population dynamics the most important programming are genetic algorithms which are inspired by the evolutionary processes of mutation, recombination, and natural selection in biology. 

Connectionist computation which is inspired by multi-cellular systems like artificial neural networks that mimic the way of working of the human brain. 

The rest of the chapter is mainly composed of five diverse examples of application of evolutionary developmental methods to problems in engineering and computer science. The chapter concludes with an attempt to foresee some future trends in EDS research and application, followed by a very short story that we hope will entertain and perhaps inspire. 

Straub, J.E. Andricioaei, I., Computational methods inspired by Tsallis statistics Monte Carlo and molecular dynamics algorithms for the simulation of classical and quantum systems, Braz. J. Phys. 1999, 29, 179-186... 

Besides the logic aspect, the chemically induced behavior of complex 5-6 connects with other macro-scale experiences such as threading/deth-reading of a needle or piston motion in a cylinder. And so it turns out that the abacus will continue to be a particular inspiration for the design of controllable molecular motions for computational purposes. Complex 5-6 illuminates this path. 

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