Evolutionary Optimization Techniques in AI: Investigating Evolutionary Optimization Techniques and Their Application in Solving Optimization Problems in AI

Authors

  • Ranadeep Reddy Palle Software Engineer, India

Keywords:

Evolutionary Optimization, Genetic Algorithms, Genetic Programming, Evolutionary Strategies, Differential Evolution, Artificial Intelligence, Optimization Problems, Machine Learning, Robotics, Data Mining

Abstract

Evolutionary optimization techniques play a vital role in solving complex optimization problems in artificial intelligence (AI). These techniques, inspired by natural evolution, have been successfully applied to various domains, including machine learning, robotics, and data mining. This paper provides an overview of evolutionary optimization techniques, including genetic algorithms, genetic programming, evolutionary strategies, and differential evolution. It explores their principles, advantages, and limitations, as well as their application in solving optimization problems in AI. The paper also discusses recent advancements and future directions in evolutionary optimization research, highlighting the potential of these techniques to further enhance the capabilities of AI systems.

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Published

20-03-2023

How to Cite

[1]
R. Reddy Palle, “Evolutionary Optimization Techniques in AI: Investigating Evolutionary Optimization Techniques and Their Application in Solving Optimization Problems in AI”, J. of Art. Int. Research, vol. 3, no. 1, pp. 1–13, Mar. 2023.

Issue

Vol. 3 No. 1 (2023): Journal of Artificial Intelligence Research

Section

Articles

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