Genetic Algorithms and their Use in the Design of Evolvable Hardware

Genetic Algorithms are an important area of Evolutionary Computing, which is a rapidly growing area of Artificial Intelligence. They are a class of algorithms which mimic the natural process of Evolution and Darwin’s principle of Survival of the Fittest – in this case, it refers to the acceptance of the best solution, generated from previous solutions by the use of genetic operators such as crossover and mutation. The next section takes a more detailed look at the background of GAs and outlines the basic concepts in its computer model. Genetic Algorithm as in the case of Darwinian model of evolution relies heavily on random experiments of reproduction. From where does this apparently simple model of problem-solving derive its power? This has been a topic of intense research work, covered in the next section. Section 3 of this paper discusses design of evolvable hardware (EHW), which is a promising approach towards autonomous and on-line reconfigurable machines capable of adapting to real-world problems.