Evaluation of Multidisciplinary Effects of Artificial Intelligence with Optimization Perspective

TL;DR

This paper discusses the multidisciplinary impacts of Artificial Intelligence, emphasizing its optimization techniques inspired by nature, and provides examples of its applications across various fields.

Contribution

It offers a comprehensive overview of intelligent optimization methods within AI and explores their diverse applications from a multidisciplinary perspective.

Findings

Intelligent optimization techniques are effective across multiple fields.

AI's optimization methods are inspired by natural and swarm behaviors.

The paper highlights the broad applicability of AI-driven optimization solutions.

Abstract

Artificial Intelligence has an important place in the scientific community as a result of its successful outputs in terms of different fields. In time, the field of Artificial Intelligence has been divided into many sub-fields because of increasing number of different solution approaches, methods, and techniques. Machine Learning has the most remarkable role with its functions to learn from samples from the environment. On the other hand, intelligent optimization done by inspiring from nature and swarms had its own unique scientific literature, with effective solutions provided for optimization problems from different fields. Because intelligent optimization can be applied in different fields effectively, this study aims to provide a general discussion on multidisciplinary effects of Artificial Intelligence by considering its optimization oriented solutions. The study briefly focuses on background of the intelligent optimization briefly and then gives application examples of intelligent optimization from a multidisciplinary perspective.