file:Playlist.dpl file:9.4.1 视频：Three Perspectives on Machine Learning.mp4 file:9.3.2 课件：Why Different Perspectives.pdf file:9.1.1 视频：What is Machine Learning.mp4 file:9.2.1 视频：History of Machine Learning.mp4 file:9.5.1 视频：Applications and Terminologies.mp4 file:12.2.1 视频：Geometric Models.mp4 file:12.4.1 视频：Networked Models.mp4 file:12.1.2 课件：Probabilistic Models.pdf file:12.3.2 课件：Logical Models.pdf file:3.2.1 视频：Example Problems.mp4 file:3.5.3 视频2：A＊ Search&Iterative Deepening A＊ Search.mp4 file:3.5.2 课件1：Best-first Search&Greedy Search.pdf file:3.3.1 视频：Searching for Solutions.mp4 file:3.1.2 课件：Problem Solving Agents.pdf file:3.6.1 视频：Heuristic Functions.mp4 file:3.4.6 课件3：Depth-first Search.pdf file:3.4.11 视频6：Comparing Uninformed Search Strategies.mp4 file:3.4.1 视频1：Breadth-first Search.mp4 file:3.4.9 视频5：Bidirectional Search.mp4 file:3.4.4 课件2：Uniform-cost Search.pdf file:3.4.8 课件4：Variants of Depth-first Search.pdf file:1.4.2 课件：The State of The Art.pdf file:1.1.3 课件：Overview of Artificial Intelligence.pdf file:1.1.1 视频：欢迎选修本课程.mp4 file:1.2.2 课件：Foundations of Artificial Intelligence.pdf folder:人工智能原理 - 北京大学 folder:9 Part V. Learning： Chapter 9. Perspectives about Machine Leaning folder:12 Part V. Learning： Chapter 12. Models in Machine Learning folder:3 Part II. Searching： Chapter 3. Solving Problems by Search folder:1 Part I. Basics： Chapter 1. Introduction folder:4 Part II. Searching： Chapter 4. Local Search and Swarm Intelligence folder:2 Part I. Basics： Chapter 2. Intelligent Agent folder:8 Part IV. Planning： Chapter 8. Classic and Real-world Planning folder:5 Part II. Searching： Chapter 5. Adversarial Search folder:6 Part II. Searching： Chapter 6. Constraint Satisfaction Problem folder:7 Part III. Reasoning： Chapter 7. Reasoning by Knowledge folder:9.4 Three Perspectives on Machine Learning folder:9.3 Why Different Perspectives folder:9.1 What is Machine Learning folder:9.2 History of Machine Learning folder:9.5 Applications and Terminologies folder:12.2 Geometric Models folder:12.4 Networked Models folder:12.1 Probabilistic Models folder:12.3 Logical Models folder:3.2 Example Problems folder:3.5 Informed Search Strategies folder:3.3 Searching for Solutions folder:3.1 Problem Solving Agents folder:3.6 Heuristic Functions folder:1.4 The State of The Art folder:1.1 Overview of Artificial Intelligence folder:1.2 Foundations of Artificial Intelligence folder:4.2 Local Search Algorithms folder:4.3 Optimization and Evolutionary Algorithms folder:4.1 Overview folder:4.4 Swarm Intelligence and Optimization folder:2.3 Task Environments folder:2.5 Category of Intelligent Agents folder:2.1 Approaches for Artificial Intelligence folder:2.4 Intelligent Agent Structure folder:2.2 Rational Agents folder:8.5 Decision-theoretic Planning folder:8.1 Planning Problems folder:8.2 Classic Planning folder:8.3 Planning and Scheduling folder:8.4 Real-World Planning folder:10.5 Dimensionality Reduction folder:10.4 Ranking folder:10.1 Classification folder:10.3 Clustering folder:10.2 Regression folder:5.6 Monte-Carlo Methods folder:5.2 Optimal Decisions in Games folder:5.1 Games folder:5.3 Alpha-Beta Pruning folder:5.4 Imperfect Real-time Decisions folder:5.5 Stochastic Games folder:6.4 Local Search for CSPs folder:6.2 Constraint Propagation： Inference in CSPs folder:6.1 Constraint Satisfaction Problems (CSPs) folder:6.5 The Structure of Problems folder:6.3 Backtracking Search for CSPs folder:11.2 Unsupervised Learning Paradigm folder:11.4 Other Learning Paradigms folder:11.3 Reinforcement Learning Paradigm folder:7.5 Bayesian Networks folder:7.3 Representation using Logic folder:7.4 Ontological Engineering folder:7.2 Knowledge Representation