Learning Automata and Their Applications to Intelligent Systems
暫譯: 學習自動機及其在智能系統中的應用

Zhang, Junqi, Zhou, Mengchu

  • 出版商: Wiley
  • 出版日期: 2023-11-30
  • 售價: $4,880
  • 貴賓價: 9.5$4,636
  • 語言: 英文
  • 頁數: 272
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1394188498
  • ISBN-13: 9781394188499
  • 相關分類: 人工智慧Algorithms-data-structures
  • 海外代購書籍(需單獨結帳)

商品描述

Comprehensive guide on learning automata, introducing two variants to accelerate convergence and computational update speed

Learning Automata and Their Applications to Intelligent Systems provides a comprehensive guide on learning automata from the perspective of principles, algorithms, improvement directions, and applications. The text introduces two variants to accelerate the convergence speed and computational update speed, respectively; these two examples demonstrate how to design new learning automata for a specific field from the aspect of algorithm design to give full play to the advantage of learning automata.

As noisy optimization problems exist widely in various intelligent systems, this book elaborates on how to employ learning automata to solve noisy optimization problems from the perspective of algorithm design and application.

The existing and most representative applications of learning automata include classification, clustering, game, knapsack, network, optimization, ranking, and scheduling. They are well-discussed. Future research directions to promote an intelligent system are suggested.

Written by two highly qualified academics with significant experience in the field, Learning Automata and Their Applications to Intelligent Systems covers such topics as:

  • Mathematical analysis of the behavior of learning automata, along with suitable learning algorithms
  • Two application-oriented learning automata: one to discover and track spatiotemporal event patterns, and the other to solve stochastic searching on a line
  • Demonstrations of two pioneering variants of Optimal Computing Budge Allocation (OCBA) methods and how to combine learning automata with ordinal optimization
  • How to achieve significantly faster convergence and higher accuracy than classical pursuit schemes via lower computational complexity of updating the state probability

A timely text in a rapidly developing field, Learning Automata and Their Applications to Intelligent Systems is an essential resource for researchers in machine learning, engineering, operation, and management. The book is also highly suitable for graduate level courses on machine learning, soft computing, reinforcement learning and stochastic optimization.

商品描述(中文翻譯)

學習自動機的綜合指南,介紹兩種變體以加速收斂和計算更新速度

學習自動機及其在智能系統中的應用 從原則、演算法、改進方向和應用的角度提供了學習自動機的綜合指南。該文本介紹了兩種變體,分別用於加速收斂速度和計算更新速度;這兩個例子展示了如何從演算法設計的角度為特定領域設計新的學習自動機,以充分發揮學習自動機的優勢。

由於噪聲優化問題在各種智能系統中普遍存在,本書詳細闡述了如何從演算法設計和應用的角度利用學習自動機來解決噪聲優化問題。

現有的最具代表性的學習自動機應用包括分類、聚類、遊戲、背包、網絡、優化、排名和排程。這些主題都有充分的討論。書中還建議了促進智能系統的未來研究方向。

本書由兩位在該領域具有豐富經驗的高素質學者撰寫,涵蓋了以下主題:


  • 學習自動機行為的數學分析,以及合適的學習演算法

  • 兩個以應用為導向的學習自動機:一個用於發現和追蹤時空事件模式,另一個用於解決線上的隨機搜尋

  • 兩種開創性的最佳計算預算分配(OCBA)方法的演示,以及如何將學習自動機與序數優化結合

  • 如何通過降低更新狀態概率的計算複雜度來實現顯著更快的收斂和更高的準確性,超越傳統的追蹤方案

在這個快速發展的領域中,學習自動機及其在智能系統中的應用 是機器學習、工程、運營和管理研究人員的重要資源。本書也非常適合研究生層次的機器學習、軟計算、強化學習和隨機優化課程。

作者簡介

JunQi Zhang, PhD, is a Full Professor with Tongji University in Shanghai. He has published 10+ papers in IEEE Transactions and 30+ papers in conferences. His current research interests include learning automata, swarm intelligence, swarm robots, multi-agent systems, reinforcement learning, and big data. MengChu Zhou, PhD, is a Distinguished Professor at New Jersey Institute of Technology. He has over 1100 publications including 14 books, 750+ journal papers (600+ in IEEE transactions), 31 patents, and 32 book-chapters. He is Fellow of IEEE, IFAC, AAAS, CAA and NAI.

作者簡介(中文翻譯)

張俊奇,博士,為上海同濟大學的正教授。他在IEEE Transactions上發表了10篇以上的論文,並在各大會議上發表了30篇以上的論文。他目前的研究興趣包括學習自動機、群體智慧、群體機器人、多代理系統、強化學習和大數據。周夢初,博士,為新澤西理工學院的特聘教授。他擁有超過1100篇的出版物,包括14本書籍、750篇以上的期刊論文(其中600篇以上發表在IEEE Transactions上)、31項專利和32章書籍章節。他是IEEE、IFAC、AAAS、CAA和NAI的會士。