Core Course offered in the third year of Bachelor of Computer Engineering in Tribhuvan University.
The main objectives of this course are:
- To provide basic knowledge of Artificial Intelligence
- To familiarize students with different search techniques
- To acquaint students with the fields related to AI and the applications of AI
- Introduction (4 hrs)
- Definition of Artificial Intelligence
- Importance of Artificial Intelligence
- AI and related fields
- Brief history of Artificial Intelligence
- Applications of Artificial Intelligence
- Definition and importance of Knowledge, and learning.
- Problem solving (4 hrs)
- Defining problems as a state space search
- Problem formulation
- Problem types, Well-defined problems, Constraint satisfaction problem,
- Game playing, Production systems.
- Search techniques (5 hrs)
- Knowledge representation, inference and reasoning (8 hrs)
- Formal logic-connectives, truth tables, syntax, semantics, tautology, validity, well-formed-formula.
- Propositional logic, predicate logic, FOPL, interpretation, quantification, horn clauses
- Rules of inference, unification, resolution refutation system (RRS) , answer extraction from RRS, rule based deduction system
- Statistical Reasoning-Probability and Bayes' theorem and causal networks, reasoning in belief network
- Structured knowledge representation (4 hrs)
- Representations and Mappings
- Approaches to Knowledge Representation
- Issues in Knowledge Representation
- Semantic nets, frames
- Conceptual dependencies and scripts
- Machine learning (6 hrs)
- Applications of AI (14 hrs)
- E. Rich and Knight, Artificial Intelligence, McGraw Hill, 1991.
- D. W. Patterson, Artificial Intelligence and Expert Systems, Prentice Hall, 2001.
- P. H. Winston, Artificial Intelligence, Addison Wesley, 1984.
- Stuart Russel and Peter Norvig, Artificial Intelligence A Modern Approach, Pearson
- Ivan Bratko, PROLOG Programming for Artificial Intelligence, Addison Wesley, 2001.
- Leon Sterling, Ehud Shapiro, The Art of PROLOG: Advanced Programming Techniques, Prentice Hall, 1996.
Laboratory exercises should be conducted in either LISP or PROLOG. Laboratory exercises must cover the fundamental search techniques, simple question answering, inference and reasoning.