Swarm Intelligence Algorithms: A Tutorial

Slowik, Adam

商品描述

Swarm intelligence algorithms are a form of nature-based optimization algorithms. Their main inspiration is the cooperative behavior of animals within specific communities. This can be described as simple behaviors of individuals along with the mechanisms for sharing knowledge between them, resulting in the complex behavior of the entire community. Examples of such behavior can be found in ant colonies, bee swarms, schools of fish or bird flocks.

Swarm intelligence algorithms are used to solve difficult optimization problems for which there are no exact solving methods or the use of such methods is impossible, e.g. due to unacceptable computational time.

This book thoroughly presents the basics of 24 algorithms selected from the entire family of swarm intelligence algorithms. Each chapter deals with a different algorithm describing it in detail and showing how it works in the form of a pseudo-code. In addition, the source code is provided for each algorithm in Matlab and in the C ++ programming language. In order to better understand how each swarm intelligence algorithm works, a simple numerical example is included in each chapter, which guides the reader step by step through the individual stages of the algorithm, showing all necessary calculations.

This book can provide the basics for understanding how swarm intelligence algorithms work, and aid readers in programming these algorithms on their own to solve various computational problems.

This book should also be useful for undergraduate and postgraduate students studying nature-based optimization algorithms, and can be a helpful tool for learning the basics of these algorithms efficiently and quickly. In addition, it can be a useful source of knowledge for scientists working in the field of artificial intelligence, as well as for engineers interested in using this type of algorithms in their work.

If the reader already has basic knowledge of swarm intelligence algorithms, we recommend the book: Swarm Intelligence Algorithms: Modifications and Applications (Edited by A. Slowik, CRC Press, 2020), which describes selected modifications of these algorithms and presents their practical applications.

商品描述(中文翻譯)

群體智能演算法是一種基於自然的優化演算法。它們的主要靈感來自於特定社群中動物的合作行為。這可以描述為個體的簡單行為以及它們之間共享知識的機制,從而產生整個社群的複雜行為。這種行為的例子可以在螞蟻群、蜜蜂群、魚群或鳥群中找到。

群體智能演算法用於解決難以找到準確解法或使用這些方法不可行的困難優化問題,例如由於計算時間過長。

本書徹底介紹了從整個群體智能演算法家族中選擇的24種演算法的基礎知識。每個章節都涉及不同的演算法,詳細描述其運作方式並以偽代碼形式展示。此外,每個演算法的源代碼都以Matlab和C++編程語言提供。為了更好地理解每個群體智能演算法的運作方式,每個章節都包含一個簡單的數值例子,逐步引導讀者通過演算法的各個階段,展示所有必要的計算。

本書可以提供理解群體智能演算法運作方式的基礎知識,並幫助讀者自行編程以解決各種計算問題。

本書對於攻讀自然優化演算法的本科生和研究生也很有用,可以成為高效快速學習這些演算法基礎知識的有用工具。此外,對於從事人工智能領域研究的科學家以及對於在工作中使用這類演算法感興趣的工程師來說,本書也是一個有用的知識來源。

如果讀者已經具備群體智能演算法的基礎知識,我們推薦閱讀《群體智能演算法:修改和應用》(A. Slowik編著,CRC Press,2020),該書描述了這些演算法的選定修改並展示了它們的實際應用。

作者簡介

Adam Slowik (IEEE Member 2007; IEEE Senior Member 2012) is an Associate Professor in the Department of Electronics and Computer Science, Koszalin University of Technology. His research interests include soft computing, computational intelligence, and, particularly, bio-inspired optimization algorithms and their engineering applications. He was a recipient of one Best Paper Award (IEEE Conference on Human System Interaction - HSI 2008).

作者簡介(中文翻譯)

Adam Slowik(2007年IEEE會員,2012年IEEE高級會員)是科茲林科技大學電子與計算機科學系的副教授。他的研究興趣包括軟計算、計算智能,尤其是生物啟發的優化算法及其工程應用。他曾獲得一項最佳論文獎(IEEE人機系統互動會議 - HSI 2008)。