Artificial neural network and Genetic programming

Shortcuts: Differences, Similarities, Jaccard Similarity Coefficient, References.

Difference between Artificial neural network and Genetic programming

Artificial neural network vs. Genetic programming

Artificial neural networks (ANNs) or connectionist systems are computing systems vaguely inspired by the biological neural networks that constitute animal brains. In artificial intelligence, genetic programming (GP) is a technique whereby computer programs are encoded as a set of genes that are then modified (evolved) using an evolutionary algorithm (often a genetic algorithm, "GA") – it is an application of (for example) genetic algorithms where the space of solutions consists of computer programs.

Similarities between Artificial neural network and Genetic programming

Artificial neural network and Genetic programming have 7 things in common (in Unionpedia): Artificial intelligence, Bio-inspired computing, Evolutionary algorithm, Fitness approximation, Gene expression programming, Genetic algorithm, Jürgen Schmidhuber.

Artificial intelligence

Artificial intelligence (AI, also machine intelligence, MI) is intelligence demonstrated by machines, in contrast to the natural intelligence (NI) displayed by humans and other animals.

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Bio-inspired computing

Bio-inspired computing, short for biologically inspired computing, is a field of study that loosely knits together subfields related to the topics of connectionism, social behaviour and emergence.

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Evolutionary algorithm

In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm.

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Fitness approximation

In function optimization, fitness approximation is a method for decreasing the number of fitness function evaluations to reach a target solution.

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Gene expression programming

In computer programming, gene expression programming (GEP) is an evolutionary algorithm that creates computer programs or models.

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Genetic algorithm

In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA).

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Jürgen Schmidhuber

Jürgen Schmidhuber (born 17 January 1963) is a computer scientist who works in the field of artificial intelligence.

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The list above answers the following questions

What Artificial neural network and Genetic programming have in common
What are the similarities between Artificial neural network and Genetic programming

Artificial neural network and Genetic programming Comparison

Artificial neural network has 329 relations, while Genetic programming has 32. As they have in common 7, the Jaccard index is 1.94% = 7 / (329 + 32).

References

This article shows the relationship between Artificial neural network and Genetic programming. To access each article from which the information was extracted, please visit:

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