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Moreover, if whole brain emulation is possible via both scanning and replicating the, at least, bio-chemical brain – as premised in the form of digital replication in The Age of Em, possibly using physical neural networks – that may have applications as or more extensive than e.g. valued human activities and may imply that society would ...
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data, and thus perform tasks without explicit instructions. [1]
In each generation, the fitness of every individual in the population is evaluated; the fitness is usually the value of the objective function in the optimization problem being solved. The more fit individuals are stochastically selected from the current population, and each individual's genome is modified ( recombined and possibly randomly ...
Traveling salesman problem and its applications [14] Stopping propagations, i.e. deciding how to cut edges in a graph so that some infectious condition (e.g. a disease, fire, computer virus, etc.) stops its spread.
Automated machine learning (AutoML) is the process of automating the tasks of applying machine learning to real-world problems. It is the combination of automation and ML. [1] AutoML potentially includes every stage from beginning with a raw dataset to building a machine learning model ready for deployment.
Industrial artificial intelligence, or industrial AI, usually refers to the application of artificial intelligence to industry and business. Unlike general artificial intelligence which is a frontier research discipline to build computerized systems that perform tasks requiring human intelligence, industrial AI is more concerned with the application of such technologies to address industrial ...
One seeks the solution of a problem in the form of strings of numbers (traditionally binary, although the best representations are usually those that reflect something about the problem being solved), [3] by applying operators such as recombination and mutation (sometimes one, sometimes both). This type of EA is often used in optimization problems.
This made for an increasing need for developing computational genomics tools, including machine learning systems, that can automatically determine the location of protein-encoding genes within a given DNA sequence (i.e. gene prediction). [40] Gene prediction is commonly performed through both extrinsic searches and intrinsic searches. [40]