Artificial life and Evolutionary computation

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Difference between Artificial life and Evolutionary computation

Artificial life vs. Evolutionary computation

Artificial life (often abbreviated ALife or A-Life) is a field of study wherein researchers examine systems related to natural life, its processes, and its evolution, through the use of simulations with computer models, robotics, and biochemistry. In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms.

Similarities between Artificial life and Evolutionary computation

Artificial life and Evolutionary computation have 9 things in common (in Unionpedia): Ant colony optimization algorithms, Artificial intelligence, Digital organism, Evolution, Evolutionary algorithm, Genetic algorithm, Genetic programming, Swarm intelligence, Universal Darwinism.

Ant colony optimization algorithms

In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.

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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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Digital organism

A digital organism is a self-replicating computer program that mutates and evolves.

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Evolution

Evolution is change in the heritable characteristics of biological populations over successive generations.

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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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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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Genetic programming

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.

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Swarm intelligence

Swarm intelligence (SI) is the collective behavior of decentralized, self-organized systems, natural or artificial.

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Universal Darwinism

Universal Darwinism (also known as generalized Darwinism, universal selection theory, or Darwinian metaphysics) refers to a variety of approaches that extend the theory of Darwinism beyond its original domain of biological evolution on Earth.

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The list above answers the following questions

What Artificial life and Evolutionary computation have in common
What are the similarities between Artificial life and Evolutionary computation

Artificial life and Evolutionary computation Comparison

Artificial life has 90 relations, while Evolutionary computation has 97. As they have in common 9, the Jaccard index is 4.81% = 9 / (90 + 97).

References

This article shows the relationship between Artificial life and Evolutionary computation. To access each article from which the information was extracted, please visit:

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