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What is an algorithm? How computers know what to do with data
Algorithms: Output
The last step of an algorithm is output - expressing the answer.
Output to a computer is usually more data. It allows computers to string algorithms together in complex ways to produce more algorithms. Output can also present information, such as putting words on a screen.
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Key Ideas
Neuroevolution
Neuroevolution is a form of artificial intelligence. It is a meta-algorithm, an algorithm for designing algorithms. It adopts the principles of biological evolution in order to design smarter algorithms. Eventually, the algorithms get pretty good at their job.
Evolutionary algorithms
Traditionally, evolutionary algorithms are used to solve specific problems. For instance, the ability to control a two-legged robot. Solutions that perform the best on some metrics are selected to produce offspring.
In spite of successes, these algorithms are more computationally intensive than approaches such as "deep learning."
The steppingstone principle
It goes beyond traditional evolutionary approaches. It explains innovation. Instead of optimizing for a specific goal, it embraces the creative exploration of a diverse population of solutions.
The steppingstone’s potential can be seen by analogy with biological evolution: feathers likely evolved for insulation and only later became handy for flight.