451: Artificial Intelligence
Course Syllabus -- Spring 1998
Professor: Janice Searleman
Office: 370 Science Center
Office Hours: M 2:00-3:00; W,F 11-12:00; Tu,Th 1:00-2:00 and
Course Objective: This course is a comprehensive introduction
to core concepts in artificial intelligence (AI), and surveys active research
areas. Topics covered are:
Text and Software:
- Search strategies: best-first search, heuristics.
- Knowledge representation using predicate logic, semantic networks,
neural nets, frames, and rules.
- Automated deduction: reasoning under uncertainty.
- Applications: problem-solving, planning, expert systems, game playing,
learning, natural language understanding.
- Artificial Intelligence: A Modern Approach , by Russell
& Norvig, Prentice-Hall, 1995. The web page associated with this textbook
is at http://www.cs.berkeley.edu/~russell/aima.html
- Allegro Common LISP (acl) will be used throughout the semester for
the programming assignments. There is a freeware version of this available
- Course handouts and assignments will be posted on the public directory
- 2 Midterms 30% (tentatively scheduled on 2/26 and 4/9)
- Final Exam 30%
- Homework & Quizzes 20%
- Projects 20%
The written homework assignments are expected to be individual
efforts, and are due in class on the date posted. Each day late will result
in 10% of the total points deducted. No assignment will be accepted more
than 4 days late. However, each student will have a total of 7 days of
automatic extensions, to be distributed as needed throughout the semester
(to accommodate travel, illness, the demands of other courses, and so
on). You are encouraged to budget your free late days as they must last
the entire semester. Unused late days will result in bonus points added
to your final grade.
The project allows you to explore in more depth an area of AI, such
as natural language understanding, computer vision, intelligent tutoring
systems, neural networks, or whatever you find most interesting. You may
work in teams of two on a project of sufficient scope, as approved by
the instructor. A brief proposal describing your project is due on Wednesday,
February 25th, and the project itself is due on Wednesday, April 29th.
You are required to demonstrate your project to the instructor during
Tentative Course Outline
- Introduction to AI: The Turing Test; Intelligent Agents.
Chapters 1 and 2
- Problem Solving: 1/24-2/12 state-Space Search; Heuristic
Search. Game Playing. Chapters 3,4 & 5
- Knowledge & Reasoning: Predicate Calculus. Inference. Forward
and Backward Chaining. Resolution. Frame Systems and Semantic Nets.
Chapters 6,7,9 & 10
- Planning: Planning Agents. Sityuation Spaces. Chapter 11
- Reasoning under Uncertainty: Probabilistic Reasoning. Belief
Networks. Decision Making. Chapters 14, 15 & 16
- Learning & Neural Nets: Inductive Learning. Decision Trees.
Feed-forward networks. Back-Propagation. Chapters 18 & 19
- Advanced Topics: Natural Language Understanding. Perception.
Speech Recognition. Chapters 22, 24, & 26
Last modified: 2 February 1998