Swarm Intelligence and Deep Evolution: Evolutionary Approach to Artificial Intelligence

This book provides a comprehensive overview of swarm intelligence and evolutionary computation, covering theoretical and practical aspects, interdisciplinary research topics, and a framework integrating them with deep learning. It reviews past and present AI research and considers future progress, with practical examples using MindRender AI educational software.

Format: Hardback
Length: 278 pages
Publication date: 14 April 2022
Publisher: Taylor & Francis Ltd

This course provides comprehensive theoretical and practical knowledge about swarm intelligence and evolutionary computation, covering interdisciplinary research topics that encompass problem-solving tasks in AI and deep learning in an easy-to-understand manner. It describes a framework, deep neuroevolution and deep swarms, that integrates swarm intelligence and evolutionary computation with deep learning. The course reviews researches in AI from the past to the present and considers the future progress of AI based on the ideas of swarm intelligence and evolution. It also shows how to learn practical tasks by neuroevolution with an AI educational software, MindRender.

Introduction:
Swarm intelligence and evolutionary computation are powerful tools for solving complex problems in various fields, including artificial intelligence, machine learning, and optimization. This course aims to provide a comprehensive understanding of these techniques and their applications.

Theoretical Foundations:
The course will begin by introducing the basic concepts of swarm intelligence and evolutionary computation. You will learn about the principles of collective behavior, swarm optimization, and genetic algorithms, and how they can be used to solve optimization problems.

Practical Applications:
In the practical sessions, you will apply the theoretical knowledge to solve real-world problems. You will work with popular programming languages such as Python and MATLAB to implement swarm intelligence algorithms and evolutionary computation techniques. You will also explore the use of these techniques in machine learning and deep learning.

Interdisciplinary Research Topics:
The course will cover interdisciplinary research topics that encompass problem-solving tasks in AI and deep learning. You will learn about topics such as neural networks, machine learning algorithms, optimization techniques, and their applications in various fields.

Future Progress of AI:
The course will also consider the future progress of AI based on the ideas of swarm intelligence and evolution. You will learn about the latest research and developments in the field and how they can be applied to solve complex problems in the future.

Conclusion:
This course provides a solid foundation in swarm intelligence and evolutionary computation, and it will equip you with the skills and knowledge to apply these techniques in real-world problems. Whether you are a student, researcher, or professional, this course will be valuable to you.

Weight: 689g
Dimension: 234 x 156 (mm)
ISBN-13: 9781032009155