Know about Evolutionary Algorithm

In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses whatever mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the persona of individuals in a population, and the cost function determines the environment within which the solutions “live”. Evolution of the accumulation then takes locates after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms; EAs are individual components that participate in an AE. Evolutionary algorithms consistently perform well approximating solutions to all types of problems because they do not make any hypothesis about the underlying fitness landscape; this generality is shown by successes in fields as diverse as engineering, art, biology, economics, marketing, genetics, operations research, robotics, social sciences, physics, and chemistry.

Apart from their use as mathematical optimizers, evolutionary procedure and algorithms have also been used as an empiric framework within which to validate theories about biological evolution and uncolored selection, particularly through work in the field of artificial life. Techniques from evolutionary algorithms applied to the modeling of biological evolution are generally limited to explorations of micro evolutionary processes; however whatever computer simulations, such as Tierra and Avida, endeavor to model macro evolutionary dynamics. A limitation of evolutionary algorithms is their lack of a clear genotype-phenotype distinction. In nature, the fertile egg cell undergoes a complex process known as embryogenesis to become a grown phenotype. This backhanded encoding is believed to make the genetic search more robust, and also may improve the evolvability of the organism. Recent work in the field of artificial embryogenesis, or artificial developmental systems, seeks to address these concerns.