"(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."

本书涵盖了人工智能的广泛领域。首先，本书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。
本书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。

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