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MASTER SYLLABUS

Master Syllabus

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Administrative Unit: Computer and Mathematical Sciences Department
Course Prefix and Number: CISS 450
Course Title: Artificial Intelligence
Number of:
Credit Hours 3
Lecture Hours 3
Lab Hours 0
Catalog Description: Concepts and theories of intelligent computer systems. Issues of perception, learning, problem solving and knowledge representation discussed. Programming in a list processing language will be required. Applications to game playing, theorem improving, expert systems, language understanding. Prerequisite: CISS 350 or 358.
 
Prerequisite(s) / Corequisite(s): CISS 350 or 358.
 
Course Rotation for Day Program: Offered even Fall.
 
Text(s): Most current editions of the following:

Artificial Intelligence: A Modern Approach
By Russell, S. J. and Norvig, P. (Prentice Hall)
Recommended
Artificial Intelligence: Structures and Strategies for Complex Problem Solving
By Luger, G. (Addison Wesley)
Recommended
 
Course Objectives
  • To learn automated reasoning and theorem proving theory.
  • To understand expert system design and machine learning issues.
  • To explore search strategies and rule--based deduction systems.
  • To investigate knowledge representation schemes.
  • To learn a language and programming techniques for artificial intelligence.
  • To investigate language understanding.
  •  
    Measurable Learning Outcomes:
  • Explain theorem-proving and automated-reasoning systems.
  • Develop state space representations for problem domains.
  • Develop state space representations for problem domains.
  • Utilize heuristic and recursive search techniques.
  • Design rule-based expert systems.
  • Discuss model-based and case-based reasoning.
  • Develop Bayesian and monotonic reasoning models.
  • Explain knowledge representation systems.
  • Program effectively in Lisp or Scheme.
  •  
    Topical Outline:
  • History and application
  • Game playing
  • Automated reasoning and theorem proving
  • Predicate calculus
  • State space design and searching
  • Expert systems
  • Knowledge representation
  • AI programming techniques
  •  
    Culminating Experience Statement:

    Material from this course may be tested on the Major Field Test (MFT) administered during the Culminating Experience course for the degree. 
    During this course the ETS Proficiency Profile may be administered.  This 40-minute standardized test measures learning in general education courses.  The results of the tests are used by faculty to improve the general education curriculum at the College.

     

    Recommended maximum class size for this course: 20

     
    Library Resources:

    Online databases are available at http://www.ccis.edu/offices/library/index.asp. You may access them from off-campus using your CougarTrack login and password when prompted.

     
    Prepared by: Lawrence West Date: September 12, 2005
    NOTE: The intention of this master course syllabus is to provide an outline of the contents of this course, as specified by the faculty of Columbia College, regardless of who teaches the course, when it is taught, or where it is taught. Faculty members teaching this course for Columbia College are expected to facilitate learning pursuant to the course objectives and cover the subjects listed in the topical outline. However, instructors are also encouraged to cover additional topics of interest so long as those topics are relevant to the course's subject. The master syllabus is, therefore, prescriptive in nature but also allows for a diversity of individual approaches to course material.

    Office of Academic Affairs
    12/04