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人工智能:探昔論今(英文版)

人工智能:探昔論今(英文版)

定 價(jià):¥258.00

作 者: 蔡自興,劉麗玨,陳白帆,王勇 編
出版社: 清華大學(xué)出版社
叢編項(xiàng):
標(biāo) 簽: 暫缺

ISBN: 9787302590972 出版時(shí)間: 2021-10-01 包裝: 平裝
開本: 16開 頁數(shù): 544 字?jǐn)?shù):  

內(nèi)容簡介

  《人工智能:探昔論今(英文版)》涵蓋了人工智能的廣泛領(lǐng)域。首先,《人工智能:探昔論今(英文版)》系統(tǒng)全面地介紹了人工智能的核心知識,包括傳統(tǒng)人工智能的基本理論和技術(shù),計(jì)算智能的基本原理和方法。其次,該書側(cè)重于發(fā)展迅速、應(yīng)用廣泛的人工智能新技術(shù),對神經(jīng)網(wǎng)絡(luò)和深度學(xué)習(xí)及其應(yīng)用進(jìn)行了較為全面的介紹。再次,該書理論與實(shí)踐高度融合,第8章至第12章列舉了人工智能的應(yīng)用實(shí)例,如專家系統(tǒng)、智能規(guī)劃、智能感知、自然語言處理等,有助于讀者對人工智能的全面理解?!度斯ぶ悄埽禾轿粽摻瘢ㄓ⑽陌妫房勺鳛楦叩仍盒O嚓P(guān)專業(yè)本科生和研究生的人工智能課程教材,也可供從事人工智能研究與應(yīng)用的科技工作者和技術(shù)人員學(xué)習(xí)參考。

作者簡介

  蔡自興,中南大學(xué)信息科學(xué)與工程學(xué)院教授,博士生導(dǎo)師,湖南省自興人工智能研究院首席科學(xué)家。曾任中國人工智能學(xué)會副理事長,智能機(jī)器人學(xué)會專業(yè)委員會主任,中國計(jì)算機(jī)學(xué)會人工智能與模式識別專業(yè)委員會委員,中國自動(dòng)化學(xué)會理事,智能自動(dòng)化專業(yè)委員會委員,IEEE 計(jì)算智能學(xué)會評審委員會委員和進(jìn)化計(jì)算技術(shù)委員會委員,曾任《智能系統(tǒng)學(xué)報(bào)》編委會副主任,《控制理論和應(yīng)用》、《機(jī)器人》、《控制與決策》、《計(jì)算技術(shù)與自動(dòng)化》、《冶金自動(dòng)化》等6家雜志編委。

圖書目錄

List of Tabies
List of Figures
About the Authors
Chapter 1.Introduction
1.1 Definition and Development of Artificial Intelligence
1.1.1 Definition of artificial intelligence
1.1.2 Origin and development of artificial intelligence
1.2 Classification of Artificial Intelligence Systems
1.3 Research Objectives and Contents of Artificial Intelligence
1.3.1 Research objectives of artificial intelligence
1.3.2 Research and application fields of artificial intelligence
1.4 Core Elements of Artificial Intelligence
1.5 Outline of the Book
References
Part 1: Knowledge-based Artificial Intelligence
Chapter 2.Knowledge Representation
2.1 State Space Representation
2.1.1 Problem state space description
2.1.2 Graph theory terminology and graphic method
2.1.3 Problem reduction representation
2.2 Knowledge Base
2.2.1 Definition and characteristics of knowledge base
2.2.2 Design and application of knowledge base
2.3 Ontology
2.3.1 Concept and definition of ontology
2.3.2 Composition and classification of ontology
2.3.3 Ontology modeling
2.4 Semantic Network Representation
2.4.1 Composition and characteristics of the semantic network
2.4.2 Representation of a binary semantic network
2.4.3 Representation of a multi-element semantic network
2.4.4 Inference process of a semantic network
2.5 Knowledge Graph
2.5.1 Definition and architecture of knowledge graph
2.5.2 Key technologies of knowledge graph
2.6 Frame Representation
2.6.1 Frame composition
2.6.2 Frame reasoning
2.7 Predicate Logic Representation
2.7.1 Predicate calculus
2.7.2 Predicate formula
2.8 Summary
References
Chapter 3.Knowledge Search and Reasoning
3.1 Graph Search Strategy
3.2 Blind Search
3.2.1 Breadth-first search
3.2.2 Depth-first search
3.2.3 Uniform cost search
3.3 Heuristic Search
3.3.1 Heuristic search strategy and valuation function
3.3.2 Ordered search
3.3.3 Algorithm A*
……
Part 2:Data-based Artificial Intelligence
Part 3:Application Examples of Artificial Intelligence

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