Topics on Artificial Intelligence

CSCI 440, fall semester, 2010

 

Instructor:    Dr. Shieu-Hong Lin

Email: shieu-hong.lin@ biola.edu

Course Website: csci.biola.edu/csci440/

Class:      M W 3:00-4:15am Business 209

Office Hours: Tuesday, Thursday 10:00-12:00, Math & CS department

 

Course objectives:[1] 

·        Establish the foundational understanding of mathematics and algorithms used in modern AI research and their applications.

·        Gain in depth understanding of AI research in speech recognition, natural language processing, data mining, machine learning, automatic reasoning, scheduling, and planning through programming assignments and .

·        Cultivate the problem solving capability and gain an in-depth understanding of the application and implementation of AI research through a series of hands-on study projects.

·        Learn the applications of scheduling and planning and how to model and solve problems by using both constraint programming techniques from AI and classical mathematical programming techniques. 

 

Textbooks:

·        Stuart Russell & Peter Norvig, Artificial Intelligence: A Modern Approach, 3rd ed. Prentice Hall, 2009.

·        J. Han, M. Kamber and J. Pei, Data Mining: Concepts and Techniques, 2nd ed. May 12, 2005, Morgan Kaufmann.

·        I.Witten & E. Frank, Weka 3: Data Mining Software in Java, 2nd ed. May 12, 2005, Morgan Kaufmann.

 

 

 

Grading Policy

1.Attendance & participation                                                              10%

2.Reading                                                                                             15%

3.Homework& programming assignments                                             45%

4.Midterm                                                                                            15%

5.Final                                                                                                  15%

 

Weekly progress reports: They are always due on Wednesdays. Download the template file from the class website. By Wednesday each week, you should spend around 5~10 minutes to add the latest progress in reading and programming made since last Wednesday into the report, and email the file to as an attachment to Dr. Lin.

 

Tentative Schedule

·        Week 1          Perspectives of artificial intelligence

·        Week 2          Intro to automatic speech recognition

·        Week 3          Probabilistic reasoning in speech recognition

·        Week 4          Intro to knowledge representation

·        Week 5          Automatic temporal reasoning

·        Week 6          AI search techniques in temporal reasoning

·        Week 7          Search techniques used in modern game programs

·        Week 8          Knowledge representation for general game

·        Week 9          Review & Midterm

·        Week 10        Intro to data mining

·        Week 11                Mining text information

·        Week 12        Supervised learning and unsupervised learning

·        Week 13        Linear regression. Naïve Bayes method. Decision-tree induction.

·        Week 14        More on classification and pattern recognition

·        Week 15        Reinforcement learning

·        Final


[1] Students desiring accommodations on the basis of physical, learning, or psychological disability for this class are to contact Disability Services.  Disability Services is located in the Learning Center (upstairs in the Biola Library) and cab e reached by calling 562-906+4542 or extension 4542 from campus.)