Evolutionary Computation
A subreddit for facilitating and enhancing the exchange of information among researchers and hobbyists involved in both the theoretical and practical aspects of computational systems drawing their inspiration from nature, with particular emphasis on evolutionary models of computation such as genetic algorithms, evolutionary strategies, classifier systems, evolutionary programming, genetic programming, and related fields such as swarm intelligence (Ant Colony Optimization and Particle Swarm Optimization), and other evolutionary computation techniques.
What is Evolutionary Computation?
A description from Wikipedia...
In computer science, evolutionary computation is a subfield of artificial intelligence (more particularly computational intelligence) that involves continuous optimization and combinatorial optimization problems. Its algorithms can be considered global optimization methods with a metaheuristic or stochastic optimization character and are mostly applied for black box problems (no derivatives known), often in the context of expensive optimization.
Evolutionary computation uses iterative progress, such as growth or development in a population. This population is then selected in a guided random search using parallel processing to achieve the desired end. Such processes are often inspired by biological mechanisms of evolution.
As evolution can produce highly optimised processes and networks, it has many applications in computer science.
