Declarative programming; problem solving; knowledge representation; reasoning; acting logically; uncertainty; learning; communicating.

Course Objectives

– To help students to conceptualize information representation and reasoning methods

– To emphasize the relatioship between problem solving and logical behavior

– To form the background for development of sophisticated applications that are capable of learning and can reason under uncertainty

Recommended or Required Reading

Russell, Stuart; Norvig, Peter; 1995; “Artificial Intelligence – A Modern Approach”; Prentice-Hall; 0-13-103805-2 ,- Luger, George F.; 1993; “Artificial intelligence: structures and strategies for complex problem solving”; Benjamin-Cummings; 0-80534-785-2

Learning Outcomes

1. Comprehension of different artificial intelligence techniques used for simulation of human behavior
2. Interpretation of traditional artificial intelligence methods based on mathematical logic
3. Construction of intelligent behavior with respect to hybrid application of artificial intelligence methods
4. Demonstration of applications with the use result-oriented languages based and hybrid techniques

Grading

Midterm 30%

Homework 30%

Final 40%