Lateral Computing - From Lateral-thinking To Lateral-computing - Transition To Lateral-computing

Transition To Lateral-computing

Lateral computing does a provocative use of information processing similar to lateral-thinking. This is explained with the use of evolutionary computing which is a very useful lateral-computing technique. The evolution proceeds by change and selection. While random mutation provides change, the selection is through survival of the fittest. The random mutation works as a provocative information processing and provides a new avenue for generating better solutions for the computing problem.

Lateral-computing takes the analogies from real world examples such as:

• How slow cooling of the hot gaseous state results in pure crystals (Annealing)
• How the neural networks in the brain solve such problems as face and speech recognition
• How simple insects such as ants and honeybees solve some sophisticated problems
• How evolution of human beings from molecular life forms are mimicked by evolutionary computing
• How living organisms defend themselves against diseases and heal their wounds
• How electricity is distributed by grids

Differentiating factors of "lateral computing":

• Does not directly approach the problem through mathematical means.
• Uses indirect models or looks for analogies to solve the problem.
• Radically different from what is in vogue, such as using "photons" for computing in optical computing. This is rare as most conventional computers use electrons to carry signals.
• Sometimes the Lateral Computing techniques are surprisingly simple and deliver high performance solutions to very complex problems.
• Some of the techniques in lateral computing use "unexplained jumps". These jumps may not look logical. The example is the use of "Mutation" operator in genetic algorithms.