Steven L Tanimoto
Principles and programming techniques of artificial intelligence: LISP, symbol manipulation, knowledge representation, logical and probabilistic reasoning, learning, language understanding, vision, expert systems, and social issues. Intended for non-majors. Not open for credit to students who have completed CSE 473. Prerequisite: CSE 373.
Introduction, Programming techniques for artificial intelligence, state-space search, knowledge representation, logical and probabilistic reasoning, learning, language understanding, image understanding, expert systems, social issues, the Python language (not Lisp).
Student learning goals
Understand basic programming techniques relevant to artificial intelligence.
Be fluent in Python.
Know fundamentals of knowledge representation, as well as the theory of problem solving with state-space search.
Understand common techniques for image understanding.
Be familiar with some of the standard approaches to natural language understanding.
General method of instruction
Lectures, labs, assignments involving both pencil-and-paper exercises and programming.
Class assignments and grading
Problem sets and programming assignments
Typically about 30% for assignments, 20% project, 25% final exam, 15% midterm exam, and 10% class participation.