Evolutionary computing is a branch of artificial intelligence that focuses on evolutionary algorithms and related techniques. It is a method of problem solving where algorithms that imitate natural selection and genetics are applied to a problem. The algorithms generate many potential solutions and then select the best ones, based on criteria that are algorithm-specific. By building on the successes of previous solutions, evolutionary computing can speed up the process of finding a solution.

Evolutionary computing operates by mimicking natural selection. A set of potential solutions is evaluated to determine which is most likely to solve the problem at hand. The algorithm then honours or penalizes the solutions to inform which of the solution set will be used in the next iteration. This process is repeated until the solutions converge on the optimal solution.

An example of evolutionary computing is the optimization of flight paths by airlines. Airline dispatchers create thousands of potential flight paths and then use evolutionary computing to select the path that avoids turbulence while minimizing fuel use and cost.

Evolutionary computing has found applications in many areas. These include biometric identification, image processing, medical diagnostics, finance, embedded systems, computer graphics, robotics, and software engineering. Moreover, it can be used in the analysis of large datasets, for pattern recognition, and for online machine learning tasks such as reinforcement learning and deep learning.

The most common techniques used in evolutionary computing are genetic algorithms, evolutionary programming, and evolution strategies. Each technique has its own distinct definition and characteristics, and they are used in different ways depending on the problem that needs to be solved.

Evolutionary computing is a rapidly developing field, combining classical AI approaches with modern software engineering and data analytics techniques. It has revolutionized the way Artificial Intelligence is used to solve problems, and its use is expected to expand in the years to come.

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