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- 授课对象: 计算机系本科生（一班）
- 教室: 仙林校区仙2-313
- 时间: 周五1-2节
- 教材: Stuart J. Russell, Peter Norvig. Artificial Intelligence: A Modern Approach (3rd edition), Pearson, 2011.
- 助教: 魏秀参
- 总评: 课程作业 + 期末考试
- 课程讨论QQ群：204071350
- 考试: 6月28日 16:30-18:30 仙1-201
Edit相关课程
建议同时选修“
机器学习”、“
数据挖掘”、“
模式识别”课
Edit作业
本次课程有四次作业，将基于GVGAI框架，请立即开始熟悉该框架：
http://www.gvgai.net
Edit课程材料
- Introduction (Download PDF)
- Search 1: Uninformed Search (Download PDF)
- Search 2: Informed Search (Download PDF)
- Search 3: Adversarial Search (Download PDF)
- Search 4: Beyond Classical Search: Bandit, Monte-Carlo Tree Search, and General Search (Download PDF)
- Search 5: Constraint Satisfaction Problems (Download PDF)
- Knowledge 1: Propositional Logic (Download PDF)
- Knowledge 2: First Order Logic (Download PDF)
- Knowledge 3: SAT, Planning and Ontology (Download PDF)
- Uncertainty 1: Bayesian Network (Download PDF)
- Uncertainty 2: Inference in Bayesian Network (Download PDF)
- Learning 1: Decision Tree (Download PDF)
- Learning 2: Neural Networks (Download PDF)
- Learning 3: Learning Principle (Download PDF)
- Learning 4: Linear Learners (Download PDF)
- Learning 5: Nearest Neighbor and Naive Bayes Classifiers (Download PDF)
- Learning 6: Feature Processing (Download PDF)
- Learning 7: MDP and Reinforcement learning (Download PDF)
- Final: On Artificial Intelligence (Download PDF)
slides are derived from Russell's in http://aima.cs.berkeley.edu/instructors.htmlEdit学术资源