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Instructor Class Description

Time Schedule:

Steven L Tanimoto
CSE 473
Seattle Campus

Introduction to Artificial Intelligence

Principal ideas and developments in artificial intelligence: Problem solving and search, game playing, knowledge representation and reasoning, uncertainty, machine learning, natural language processing. Not open for credit to students who have completed CSE 415. Prerequisite: CSE 326 or CSE 332; recommended: CSE 312; either STAT 390, or STAT 391.

Class description

Knowledge representation techniques, including the use of ISA hierarchies, logic, the Python programming language, and the PROLOG language. State-space search methods. Problem formulation and solving. Logical and probabilistic inference methods. Machine learning, natural language understanding, and image understanding.

Student learning goals

Formulate problems in order to apply state-space, logical, and probabilistic solution methods.

Program solution methods in Python or PROLOG.

Understand the strengths and limitations of automatic problem solving methods.

Understand key concepts of machine learning, natural language understanding, and image understanding.

General method of instruction

Lectures, assignments

Recommended preparation

CSE 326. CSE 341 is recommended but not required. Programming experience. (Previous exposure to Python is not required.)

Class assignments and grading

Problem sets, including programming in Python and PROLOG.

Tests and assignments.


The information above is intended to be helpful in choosing courses. Because the instructor may further develop his/her plans for this course, its characteristics are subject to change without notice. In most cases, the official course syllabus will be distributed on the first day of class.
CSE 473 website
Last Update by Steven L Tanimoto
Date: 03/25/2010