Artificial Intelligence, A Modern Approach, latest edition by Stuart Russell and Peter Norvig, Prentice-Hall.
Additional reading provided/assigned by instructor.
Knowledge systems are intelligent systems that totally or partially involve computational representation and processing of knowledge.
Objectives of this class are to:
- Introduce students to the principles and techniques for engineering and developing knowledge systems
- Teach the alternative computational structures and methods for representation of knowledge
- Teach procedures and algorithms for computational processing (of knowledge structures), including automated reasoning and inference from knowledge, learning new knowledge, handling uncertain information, and complex knowledge-based-decision-making
- Discuss alternative system architectures (engines) for knowledge-based systems
Graduate-level requirements include a more extensive and in-depth project, and an additional assignment or question on the exam
- Homework: 3 assignments
- Project: 1 class project
- Activities: A few class activities
- Exams: 1 midterm exam, 1 final exam
- Typical grading policy: 25% midterms, 25% final exam, 20% homework, 10% activities, 20% class project