Time Schedule:
Steven L Tanimoto
CSE 473
Seattle Campus
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.
