人工智能课程主页

Information

• 授课对象: 计算机系本科生
• 教室: 仙林校区仙2-117
• 时间: 周五3-4节 ＋ 双周周三1-2节
• 教材: Stuart J. Russell, Peter Norvig. Artificial Intelligence: A Modern Approach (3rd edition), Pearson, 2011.
• 助教: 杨敬文
• 总评: 课程作业 + 期末考试

作业

• >>>作业1: 推盒子游戏>>> 截止日期: 3月26日晚上8点整
• >>>作业2: 黑白棋游戏>>> 截止日期: 4月16日晚上8点整
• >>>作业3: Mr.PacMan游戏>>> 截止日期: 7月10日晚上8点整

课程材料

1. Introduction (Download PDF)
2. Search 1: Uninformed Search (Download PDF)
3. Search 2: Informed Search (Download PDF)
4. Search 3: Iterative-Improvement Methods (Download PDF)
5. Search 4: Adversarial Search (Download PDF)
6. Search 5: Constraint Satisfaction Problems (Download PDF)
7. Knowledge 1: Propositional Logic (Download PDF)
8. Knowledge 2: First Order Logic (Download PDF)
9. Knowledge 3: SAT, Planning, Ontology (Download PDF)
10. Uncertainty 1: Probability and Bayesian Network (Download PDF)
11. Uncertainty 2: Inference in Bayesian Network (Download PDF)
12. Uncertainty 3: Inference with Time (Download PDF)
13. Learning 1: Decision Tree Learning (Download PDF)
14. Learning 2: Neural Networks (Download PDF)
15. Learning 3: Learning Principle (Download PDF)
16. Learning 4: Linear Models (Download PDF)
17. Learning 5: Nearest Neighbors, Naive Bayes, and Ensemble Learning (Download PDF)
18. Learning 6: Feature Processing (Download PDF)

学术资源

• 人工智能领域学术期刊/杂志：
  • Artificial Intelligence
  • AI Magazine
  • Artificial Intelligence Review
  • IEEE Intelligent Systems
  • ACM Transactions on Intelligent Systems and Technology
• 人工智能领域学术会议
  • IJCAI
  • AAAI
  • ECAI
  • PRICAI
  • Aus-AI