CS 455 - Artificial Intelligence

Description:
Introduction to the principles of artificial intelligence. Pattern matching, knowledge representation, natural language processing, expert systems.

Prerequisites:
Prerequisites: CS 302, CS 325, CS 362 and MATH 330, with a grade of C or higher in each course.

Credits: (4)

Learner Outcomes:
Upon successful completion of this course, the student will be able to:

List the historical developments of artificial intelligence
Describe and apply the elements of production and matching
- productions system methodology
- pattern matching
- mathematical formula
- manipulation
- the notion of unification
Describe and apply the elements used in knowledge representation
- productions rules
- concept hierarchies
- inheritance
- propositional and predicate logic
- frames of context
- semantic networks
- constraints
- relational databases
Describe and apply the elements used in searching
- elementary search techniques
- heuristic search techniques
- planning
- two-person, zero-sum games
Describe and apply the elements used in probabilistic reasoning
- probability
- probabilistic inference networks
- updating inference networks
- the Dempster-Shafer calculus
Describe and apply the elements used in learning
- classification rules
- general rules from fixed examples
- self-directed conceptualization systems
Describe and apply the elements used in natural language understanding
- syntax
- semantics and representation
- computing interpretations
- dialog management
Describe and apply the elements used in expert systems
- integration of Al techniques
- tools
- hardware

Learner Outcomes Approval Date:
4/3/20

Anticipated Course Offering Terms and Locations: