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Join Tina Tian's Artificial Intelligence course to learn about heuristic search, natural language processing, computer vision, robotics, and more. Prepare for exams, complete homework, and work on group projects.
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CMPT 420 / CMPG 720Artificial Intelligence Instructor: Tina Tian
About me • Email: tina.tian@manhattan.edu • Office: RLC 203 • Office Hours: Tuesday, Friday 3:30 – 5:00 PM • or by appointment • Website: turing.manhattan.edu/~tina.tian
About the Course • Tue, Fri 11:00–12:15 • Prerequisite: CMPT 238 • Textbook: • Artificial Intelligence: A Modern Approach (AIMA), 3rd Edition, by Stuart Russell and Peter Norvig, Prentice Hall, 2010. ISBN: 0136042597
Grading • Midterm Exam (in class) 20% • Final Exam 30% • Homework 25% • Projects 25%
Homework • Writing problems • Hard copy • Except for graphs, trees, etc. • Strict deadline! • Due in a week after being announced • Late homework will not be accepted
Homework • You may discuss the homework with other students. • However, you must independently write up your own solutions.
Projects • CMPT 420 • Group work • Maximum 3 students • CMPG 720 • Individual work
Projects • Programming • C++, Java or Python • Submitted to Moodle (lms.manhattan.edu) • One submission per group • No partial credit is given to projects. • Due by the last day of class (May 3)
What to submit • Readme.doc • Algorithm chosen (if applicable) • Explanation of functions and data structures used • Input and output format (give an example) • Source code and executable files (.zip) • .cpp and .exe • .java and .class • .py • zip the whole project folder if you are using Eclipse, NetBeans or VS
Advices • Take notes • Start the homework and projects early
What AI covers • 1997 game between the chess champion Garry Kasparov and DEEP BLUE • Asimo humanoid robot • Thomas Bayes (1702 – 1761) • Mars Exploration Rover (2004 - ) • Alan Turing (1912 – 1954) • Shakey (1966 – 1972) with its project leader Charles Rosen (1917 – 2002) • Aristotle (384 B.C. – 322 B.C.) and his planning algorithm in original Greek • Bayesian network for medical diagnosis
Subfields of AI • Heuristic Search • Adversarial Search (Games) • Natural Language Processing • Knowledge Representation • Computer Vision • Robotics • Planning • Learning • ...
What you will learn • Introduction of AI and intelligent agents • Searching algorithms • Uninformed search, informed search, local search
What you will learn • Game tree • Backtracking • (CSP)
What you will learn • Machine learning • Decision tree • Weka
Reading • AIMA Chapter 1