Artificial Intelligence
Year / Semester: 
4th Semester

Explain the basic knowledge representation, problem solving, and learning methods of Artificial Intelligence.


Introduction and Overview

Neural Networks

Principles of Knowledge Representation

Artificial Intelligence Programming

Expert system

• Expert Systems Overview

• What is an expert system?

• Expert system cu\component

• Application of expert system

• Different between an Expert System and a traditional system

• Advantages and Disadvantages

• Monitoring and Control

• Limitations of expert systems


The Language of First Order Logic Higher Order Logic Models and Entailment Deduction, Soundness and Completeness Conjunctive Normal Form Clausal Form Resolution Unification

The Prolog Language

Section 1 - Prolog as a Relational Language A Relational Language Prolog Procedures Pattern Matching List Processing Examples

Section 2 - Prolog as a Non-deterministic Language User-defined Tests Generate and Test

Section 3 - Prolog as a Database language The Prolog Database

Section 4 - Further Prolog Features An Example: Binary Trees Defining Infix Operators Input and Output in Prolog Changing the Database Further Control Structures

Section 5 - Graphs and Searching in Prolog Representing Graphs in Prolog A Breadth-First Solution A Best-First Solution

Section 6 - Advanced Programming Techniques

Semantic nets and frames

Semantic nets Inheritance Reification Frames, Slots and Fillers Demons and Object-Oriented Programming Defaults and Overrides Multiple Inheritances

Reasoning with uncertainty

Probabilistic reasoning Fuzzy logic Truth maintenance Doyle’s Truth Maintenance System

Suggested Readings: 

Artificial intelligence By Rich,E. ; Knight, Kevin TMH