本书是面向人工智能专业英语课程的教材，全书共分为10个单元，分别为人工智能介绍、知识表示和推理、不确定性推理、人工智能的搜索方法、机器学习、人工神经网络、深度学习、强化学习、计算机视觉和自然语言处理。本书信息量大，知识性强，注重英语的听、说、读、写、译能力的全面培养和实际应用。各单元内容均分为阅读与翻译、写作、听与说三大部分；采用场景式教学和体验式学习相结合的方式，融合了角色扮演、多人会话和小组讨论等行之有效的训练方法。 本书适合国内各类高校智能科学与技术、计算机科学与技术、软件工程等相关专业教学之用，也可作为其相关专业或IT领域人员的自学参考用书。

Unit 1 Introduction to Artificial Intelligence
Part 1 Reading & Translating
Section A: The Turing Test
Section B: Benefits and Risks of Artificial Intelligence
Part 2 Simulated Writing: Uncovering the Secrets of Clear Writing (I)
Part 3 Listening & Speaking
Dialogue: Artificial Intelligence
Listening Comprehension: Thinking Machines
Dictation: Intelligent Agent
Unit 2 Knowledge Representation and Reasoning
Part 1 Reading & Translating
Section A: Representing and Manipulating Knowledge
Section B: Learning
Part 2 Simulated Writing: Uncovering the Secrets of Clear Writing (II)
Part 3 Listening & Speaking
Dialogue: Knowledge Representation and Reasoning
Listening Comprehension: Logical Reasoning
Dictation: Semantic Networks
Unit 3 Reasoning with Uncertainty
Part 1 Reading & Translating
Section A: Reasoning with Uncertainty
Section B: Probabilistic Reasoning
Part 2 Simulated Writing: Communicating with Social Media
Part 3 Listening & Speaking
Dialogue: Reasoning with Uncertainty
Listening Comprehension: Fuzzy Logic
Dictation: Bayesian Network
Unit 4 Search Methods in Artificial Intelligence
Part 1 Reading & Translating
Section A: Heuristic Search
Section B: Genetic Algorithms
Part 2 Simulated Writing: Using Presentation Software to Write
Part 3 Listening & Speaking
Dialogue: Search Methods in Artificial Intelligence
Listening Comprehension: A* Search
Dictation: Heuristic Search Techniques
Unit 5 Machine Learning
Part 1 Reading & Translating
Section A: Decision Tree in Machine Learning
Section B: Kmeans Clustering Algorithm and Example
Part 2 Simulated Writing: Developing Reports and Proposals(I)
Part 3 Listening & Speaking
Dialogue: Machine Learning
Listening Comprehension: Supervised Learning
Dictation: Unsupervised Learning
Unit 6 Artificial Neural Networks
Part 1 Reading & Translating
Section A: Artificial Neural Networks
Section B: Handwritten Digit Recognition
Part 2 Simulated Writing: Developing Reports and Proposals(II)
Part 3 Listening & Speaking
Dialogue: Artificial Neural Network
Listening Comprehension: Training Artificial Neural Networks
Dictation: Applications of Neural Networks
Unit 7 Deep Learning
Part 1 Reading & Translating
Section A: Deep Learning，Machine Learning，and AI
Section B: Convolutional Neural Network
Part 2 Simulated Writing: Writing Professional Letters (I)
Part 3 Listening & Speaking
Dialogue: Deep Learning
Listening Comprehension: Generative Adversarial Network
Dictation: Recurrent Neural Network
Unit 8 Reinforcement Learning
Part 1 Reading & Translating
Section A: Reinforcement Learning，Deep Learnings Partner
Section B: AlphaGo Zero: Starting from Scratch
Part 2 Simulated Writing: Writing Professional Letters (II)
Part 3 Listening & Speaking
Dialogue: Reinforcement Learning
Listening Comprehension: Deep Reinforcement Learning
Dictation: Reinforcement Learning Challenges
Unit 9 Computer Vision
Part 1 Reading & Translating
Section A: Whats the Difference between Computer Vision，
Image Processing and Machine Learning?
Section B: Using Vision for Controlling Movement
Part 2 Simulated Writing: Writing for Employment (I)
Part 3 Listening & Speaking
Dialogue: Computer Vision
Listening Comprehension: Pattern Recognition
Dictation: Artificial Intelligence，Machine Learning，Deep Learning，
and Computer Vision...What is the Difference？
Unit 10 Natural Language Processing
Part 1 Reading & Translating
Section A: Language Understanding
Section B: Natural Language Processing vs．Machine Learning vs．
Deep Learning
Part 2 Simulated Writing: Writing for Employment (II)
Part 3 Listening & Speaking
Dialogue: Natural Language Processing
Listening Comprehe