CS 305: Artificial Intelligence

Course Description:

The student will learn the terminology and methods used in a variety of artificial intelligence areas.These topics will be covered: history of artificial-intelligence, search techniques, knowledge representation. In addition, one or more of these topics will be covered: expert systems, uncertainty, case-based reasoning, neural networks, vision, robotics. The student may use various AI tools, Lisp, and/or Prolog for AI projects. Prerequisite: CS 352. 3:0:3

Learning Outcomes:

Upon completion of this course the student should be able to:

1. Explain the history of artificial intelligence.
2. Explain and trace various search algorithms.
3. Solve first-order logic problems.
4. Explain knowledge representation techniques.
5. Do one or two of these:
   • Solve problems involving uncertainty.
   • Explain and trace machine learning techniques including neural network learning.
   • Explain and analyze vision concepts.
   • Explain and analyze robotics concepts.
6. Write programs that implement artificial intelligence algorithms for some of the learning outcomes items.
   See below "Additional Information" section regarding the use of Lisp as the implementation language.

Assessment Measures:

Assessment Tool	Linkage to Learning Outcome #:
Homework Assignments:
Assign a sufficient amount of homework such that all of the above objectives are covered.	All
For each homework assignment, include short answer questions that require the student to apply the above objectives.	1-5
For certain homework assignments, the student will be asked to solve a problem(s) by applying an appropriate artificial intelligence algorithm.	2-6
For certain homework assignments, the student will be asked to analyze or trace an artificial intelligence algorithm.	2-5
For certain homework assignments, the student will be asked to implement an artificial intelligence algorithm with a working program.	6
Exams:
Include one or more of: short answer, multiple choice, algorithm trace.	1-5
Given a problem description, apply an appropriate artificial intelligence algorithm.	2-5
Given a problem description, write a solution using pseudocode or a programming language.	6

Textbooks:

To view the approved textbook list, click here.

Additional Information:

Instructors are strongly encouraged to assign several programming projects that implement AI concepts. Instructors may require students to use Lisp since compilers for those three languages are installed on Park's lab computers. Optionally, students may want to download a free trial version of Lisp here: http://www.franz.com