Machine learning - Deepstash

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What is an algorithm? How computers know what to do with data

Machine learning

It can sometimes be too complicated to spell out a decision-making process. Machine learning tries to "learn" based on a set of past decision-making examples.

Machine learning is used for things like recommendations, predictions, and looking up information.

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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.