(1) 《Artificial Intelligence：From Beginning to Date》 comprehensively covers the technical content of artificial intelligence. It not only discusses knowledge-based artificial intelligence with a certain space, but also highlights data-based artificial intelligence content with a larger space, so that readers have a more comprehensive understanding of artificial intelligence from ancient times to the present.

(2) 《Artificial Intelligence：From Beginning to Date》focuses on the new technology of artificial intelligence that has been rapidly developed and widely used in recent years. It provides a relatively comprehensive introduction to deep neural networks and deep learning and their applications, which can be used as a research guide for readers to learn and refer to.

(3)In addition to discussing the technical content of artificial intelligence, 《Artificial Intelligence：From Beginning to Date》discusses on some general issues of artificial intelligence in the new era, such as the core technology and role of artificial intelligence, industrialization of artificial intelligence, the benefits and safety of artificial intelligence, which will help readers expand their horizons and enhance their comprehensive understanding of artificial intelligence.

　　《人工智能：探昔论今（英文版）》涵盖了人工智能的广泛领域。首先，《人工智能：探昔论今（英文版）》系统全面地介绍了人工智能的核心知识，包括传统人工智能的基本理论和技术，计算智能的基本原理和方法。其次，该书侧重于发展迅速、应用广泛的人工智能新技术，对神经网络和深度学习及其应用进行了较为全面的介绍。再次，该书理论与实践高度融合，第8章至第12章列举了人工智能的应用实例，如专家系统、智能规划、智能感知、自然语言处理等，有助于读者对人工智能的全面理解。
　　《人工智能：探昔论今（英文版）》可作为高等院校相关专业本科生和研究生的人工智能课程教材，也可供从事人工智能研究与应用的科技工作者和技术人员学习参考。

蔡自兴，中南大学信息科学与工程学院教授，博士生导师,湖南省自兴人工智能研究院首席科学家。曾任中国人工智能学会副理事长，智能机器人学会专业委员会主任，中国计算机学会人工智能与模式识别专业委员会委员，中国自动化学会理事，智能自动化专业委员会委员，IEEE 计算智能学会评审委员会委员和进化计算技术委员会委员，曾任《智能系统学报》编委会副主任，《控制理论和应用》、《机器人》、《控制与决策》、《计算技术与自动化》、《冶金自动化》等6家杂志编委。

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

　　In May 1983， I went to Purdue University in the United States to study arti.cial intelligence under the direction of Professor K.S. Fu， a member of the National Academy of Engineering Sciences， an international pioneer in arti.cial intelligence， and the father of international pattern recognition. Under the advice and guidance of Academician K.S. Fu， Guangyou Xu， and I edited and wrote a book， Arti.cial Intelligence and Its Applications.It was published by Tsinghua University Press in 1987 and became the .rst published arti.cial intelligence book with independent intellectual property rights in China. This book has played a major role in promoting the spread and development of arti.cial intelligence in China in the past 35 years. I deeply miss and thank Professor Fu， Professor Wenjun Wu and Professor Tong Chang， and deeply thank to Dr. Jian Song and Professor Yanda Li.
　　As a frontier and interdisciplinary subject， arti.cial intelligence has been advancing with the times along with the progress of world society and the development of science and technology. It has made great progress in the past 60 years. In recent years， a new round of arti.cial intelligence research and entrepreneurial climax has emerged， pushing the development of arti-.cial intelligence into a new era. New arti.cial intelligence algorithms rep-resented by deep learning promote the widespread application of arti.cial intelligence， and the industrialization of arti.cial intelligence has also risen to new heights.
　　At present， there is a lack of monographs at home and abroad that fully re.ect the latest developments in arti.cial intelligence. People hope to have such a book available. The book should not only have a novel system architecture， fully re.ect the scienti.c and technological connotation of arti-.cial intelligence， but also highlight the innovative development of arti.cial intelligence and guide its application. WSPC advised us to publish a new monograph on arti.cial intelligence at the right time. After reviewing and discussing our Publication Proposal， on the recommendation of AI experts
　　such as Dr. A. Ng and Dr. J.H. Zheng， as well as the recommendation of IEEE Fellow Dr.YC Jin and IEEE Fellow Dr. L.C. Jiao， the publishers agreed to compile and publish a new arti.cial intelligence monograph named Arti.-cial Intelligence： From Beginning to Date， and proposed a new architecture and related content.
　　This book covers a wide range of topics in arti.cial intelligence and has three characteristics. First， this book is a systematic and comprehen-sive book covering the core technologies of arti.cial intelligence， includ-ing the basic theories and techniques of “traditional” arti.cial intelligence， and the basic principles and methods of computational intelligence. Sec-ondly， this book pays attention to innovation， focusing on the introduction of machine learning， especially deep learning technology and other arti.cial intelligence learning methods that have been widely used in recent years. Third， the theory and practice of this book are highly integrated. There are theories， techniques， methods， and many examples of deep learning appli-cations that can help readers understand the theory of arti.cial intelligence and its application development.
　　This book is divided into three parts， following the introductory Chapter 1， which describes the de.nition， classi.cation， origin， and devel-opment of arti.cial intelligence， introduces the research objectives and main contents of arti.cial intelligence， and lists the research and applica-tion .elds of arti.cial intelligence.The .rst part is knowledge-based arti.cial intelligence， including Chapters 2 to 4; Chapters 2 and 3 study the knowl-edge representation method and search inference technology of arti.cial intelligence， and Chapter 4 discusses knowledge-based machine learn-ing. Part 2 is data-based arti.cial intelligence， including Chapters 5 to 7; Chapters 5 and 6 introduce neural computing and evolutionary computing， respectively， and Chapter 7 discusses data-based machine learning. Part 3 contains application examples of arti.cial intelligence， including Chapters 8 to 11， elaborating on the important application areas of arti.cial intelligence in each of the following： expert system， intelligent planning， intelligent per-ception （including pattern recognition and speech recognition）， and natural language processing， etc.， with special attention being paid to introduce the application of deep learning in various related .elds. The last chapter， Chapter 12， is the prospect of arti.cial intelligence， involving the impact of arti.cial intelligence on humans， the deep integration of arti.cial intel-ligence technology， and the industrialization of arti.cial intelligence. This book is a practical guide for arti.cial intelligence research and development personnel， and a valuable reference book for undergraduate and graduate students to learn arti.cial intelligence.