Lectures on Intelligent Systems
暫譯: 智能系統講座

Vanneschi, Leonardo, Silva, Sara

Lectures on Intelligent Systems
  • 出版商: Springer
  • 出版日期: 2023-01-14
  • 售價: $2,970
  • 貴賓價: 9.5 折 $2,822
  • 語言: 英文
  • 頁數: 349
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 3031179218
  • ISBN-13: 9783031179211

    • 海外代購書籍(需單獨結帳)

相關主題

商品描述

This textbook provides the reader with an essential understanding of computational methods for intelligent systems. These are defined as systems that can solve problems autonomously, in particular problems where algorithmic solutions are inconceivable for humans or not practically executable by computers. Despite the rapidly growing applications in this field, the book avoids application details, instead focusing on computational methods that equip the reader with the methodological tools and competencies necessary to tackle current and future complex applications.

The book consists of two parts: computational intelligence methods for optimization, and machine learning. Part I begins with the concept of optimization, and introduces local search algorithms, genetic algorithms, and particle swarm optimization. Part II begins with an introduction to machine learning and covers several methods, many of which can be used as supervised learning algorithms, such as decision tree learning, artificial neural networks, genetic programming, Bayesian learning, support vector machines, and ensemble methods, plus a discussion of unsupervised learning.

This textbook is written in a self-contained style, suitable for undergraduate or graduate students in computer science and engineering, and for self-study by researchers and practitioners.

商品描述(中文翻譯)

這本教科書為讀者提供了智能系統計算方法的基本理解。這些系統被定義為能夠自主解決問題的系統，特別是那些對人類來說無法想像的算法解決方案或對計算機來說不切實際的執行問題。儘管該領域的應用迅速增長，本書避免了應用細節，而是專注於計算方法，為讀者提供必要的方法論工具和能力，以應對當前和未來的複雜應用。

本書分為兩部分：優化的計算智能方法和機器學習。第一部分從優化的概念開始，介紹了局部搜索算法、遺傳算法和粒子群優化。第二部分從機器學習的介紹開始，涵蓋了幾種方法，其中許多可以用作監督學習算法，例如決策樹學習、人工神經網絡、遺傳編程、貝葉斯學習、支持向量機和集成方法，並討論了非監督學習。

這本教科書以自足的風格撰寫，適合計算機科學和工程的本科生或研究生，以及研究人員和實踐者的自學。

作者簡介

Leonardo Vanneschi is a Full Professor at the Nova Information Management School (NOVA IMS) of the Universidade Nova de Lisboa, Portugal. His main research interests involve machine learning, data science, optimization, complex systems and, in particular, evolutionary computation. He has published more than 200 contributions, 11 of which have been recognized with international awards. In 2015, he received the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe. In 2020, he was included in the list of the top 2% world researchers in a study carried out by Stanford University.

Sara Silva is a Principal Investigator at the Computer Science and Engineering Research Centre (LASIGE) of the Universidade de Lisboa, Portugal. Her main research interests are machine learning and evolutionary computation, including interdisciplinary applications in the areas of remote sensing and bioinformatics. She is the author of around 100 peer-reviewed publications, having received more than 10 nominations and awards for best paper and best researcher. In 2018 she received the Evo* Award for Outstanding Contribution to Evolutionary Computation in Europe. She created the MATLAB Genetic Programming Toolbox (GPLAB).


作者簡介(中文翻譯)

Leonardo Vanneschi 是葡萄牙里斯本新大學 (Universidade Nova de Lisboa) 新資訊管理學院 (NOVA IMS) 的全職教授。他的主要研究興趣包括機器學習、數據科學、優化、複雜系統，特別是進化計算。他已發表超過200篇學術貢獻，其中11篇獲得國際獎項的認可。2015年，他因對歐洲進化計算的傑出貢獻而獲得 Evo* 獎。2020年，他被斯坦福大學的一項研究列入全球前2%的研究人員名單。

Sara Silva 是葡萄牙里斯本大學 (Universidade de Lisboa) 計算機科學與工程研究中心 (LASIGE) 的首席研究員。她的主要研究興趣是機器學習和進化計算，包括在遙感和生物信息學領域的跨學科應用。她是約100篇經過同行評審的出版物的作者，並獲得超過10項最佳論文和最佳研究者的提名與獎項。2018年，她因對歐洲進化計算的傑出貢獻而獲得 Evo* 獎。她創建了 MATLAB 遺傳編程工具箱 (GPLAB)。

類似商品