You're reading from Hands-On Genetic Algorithms with Python

Product typeBook

Published inJan 2020

Reading LevelIntermediate

PublisherPackt

ISBN-139781838557744

Edition1st Edition

Languages

Python

Tools

Keras TensorFlow

Concepts

Artificial Intelligence

Author (1)

Eyal Wirsansky

Differences from traditional algorithms

There are several important differences between genetic algorithms and traditional search and optimization algorithms, such as gradient-based algorithms.

The key characteristics of genetic algorithms distinguishing them from traditional algorithms are:

Maintaining a population of solutions
Using a genetic representation of the solutions
Utilizing the outcome of a fitness function
Exhibiting a probabilistic behavior

In the upcoming sections, we will describe these factors in greater detail.

Population-based

The genetic search is conducted over a population of candidate solutions (individuals) rather than a single candidate. At any point in the search, the algorithm retains a set of...

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Author (1)

Eyal Wirsansky

Eyal Wirsansky is a senior data scientist, an experienced software engineer, a technology community leader, and an artificial intelligence researcher. Eyal began his software engineering career over twenty-five years ago as a pioneer in the field of Voice over IP. He currently works as a member of the data platform team at Gradle, Inc. During his graduate studies, he focused his research on genetic algorithms and neural networks. A notable result of this research is a novel supervised machine learning algorithm that integrates both approaches. In addition to his professional roles, Eyal serves as an adjunct professor at Jacksonville University, where he teaches a class on artificial intelligence. He also leads both the Jacksonville, Florida Java User Group and the Artificial Intelligence for Enterprise virtual user group, and authors the developer-focused artificial intelligence blog, ai4java.
Read more about Eyal Wirsansky

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