Course FormatCourse Goals
Textbooks and References
Prerequisites by Topic
Major Topics Covered in Course
Focuses on approaches to making computers act intelligently by studying current methods for automated understanding, problem solving, optimal search, knowledge representation, vision, and learning. Students perform experiments with semantic nets, logical deduction systems, evidential reasoning systems, and/or neural net.
4 QH credit
Prerequisite: COM 1201, COM 1340.
Course is offered only during the Winter quarter. CS majors are guaranteed a place in class.
This is an elective course for BS CS majors, a 'focused elective' course for BA CS majors, and an elective for BS IS majors.
Professor Ronald Williams and Carole Hafner
firstname.lastname@example.org and email@example.com
Algorithms and Data Structures II
Lisp programming (now part of the Recursive Thinking course).
Problem solving through search, including informed search and game playing Reasoning agents, inference in first-order logic, and the use of first-order logic to describe to describe situations in the world Planning
Completing and running a Lisp program to solve water-jug puzzles, given instructor-supplied code for performing iterative-deepening depth-first search. (2 weeks) Completing and running a Lisp program to find shortest 8-puzzle solutions, given instructor-supplied code for performing A* search. This included testing three different heuristic functions and reporting number of nodes expanded using each. (2 weeks) Encoding some simple knowledge in the form of "facts" and "rules" and running instructor-supplied forward and backward chaining programs on them. (2 weeks)