May 1, 2018


BY :     May 1, 2018

Biological evolution is the process describing how organisms evolve over time to adapt to the environment for better survival. This adaption happens in a most optimal way possible and the definition of optimality is quite dynamic decided by the environment. Definitely, to develop such adaption is the result of a very long learning process evolving as a part of fundamental natural instincts. Understanding the way it happens across generations can be leveraged effectively for many AI applications in practice. A large class of such applications is contributed by selection of optimal alternative over large other options and learning such optimal alternatives through experimentations. Genetic algorithms represent such natural evolution process.

Read more about the basics of GA with the illustration in the whitepaper, here.

Umesh Hivarkar


Characterized by multidisciplinary skills, having unique combination of R&D profile, academics, and industry, spanning over 24+ years of experience. Doctoral research in fiber optics & sensors, Instrumentation, Integrated optics, and Modeling & Simulation. Core expertise in modeling and simulation, analytics, process & system automation and control, Maths and statistical analysis, application specific algorithm development, Machine vision, global optimization techniques, integrated optics, data acquisition/signal conditioning, radar signals and systems, speech/voice processing, data mining, PC based instrumentation.

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*Opinions expressed on this blog reflect the writer’s views and not the position of the Sogeti Group