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Modified: 2015/06/17 07:24 by
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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
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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
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课程材料
Introduction (
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)
Search 1: Uninformed Search (
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)
Search 2: Informed Search (
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)
Search 3: Iterative-Improvement Methods (
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)
Search 4: Adversarial Search (
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)
Search 5: Constraint Satisfaction Problems (
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)
Knowledge 1: Propositional Logic (
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)
Knowledge 2: First Order Logic (
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)
Knowledge 3: SAT, Planning, Ontology (
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)
Uncertainty 1: Probability and Bayesian Network (
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)
Uncertainty 2: Inference in Bayesian Network (
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)
Uncertainty 3: Inference with Time (
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)
Learning 1: Decision Tree Learning (
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)
Learning 2: Neural Networks (
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)
Learning 3: Learning Principle (
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)
Learning 4: Linear Models (
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)
Learning 5: Nearest Neighbors, Naive Bayes, and Ensemble Learning (
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)
Learning 6: Feature Processing (
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)
slides are derived from Russell's in http://aima.cs.berkeley.edu/instructors.html
slides for reference
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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
The end