Introduction to Artificial Intelligence Heshaam Faili University of Tehran

2 Course logistics Intended for CS students Software related Artificial intelligence postgraduate Grading: Midterm exam: 30 % Final exam: 40 % Others Exercises & small projects: 15 % Quizzes: in TA class, 2 in main class (5-10%) Two main Projects: (10-20%) Contest (GAME Playing) Final Project

3 Course references Textbook: Artificial Inteligence: A Modern Approach: by S. Russell and P. Norvig, Prentice Hall, 1995(2003) Artificial Intelligence: by Elain Rich and Kevin Knight, Mc-Graw Hill, Programming in PROLOG, Clocksin and Mellish (1981) Other AI Related text books and papers..

4 Course goals Learn a set of concepts, ways of thinking, methods, and algorithms applicable to help in solving a wide range of real-life problems Learn how to formulate and describe problems Acquire a new set of programming skills Set the basis for advanced courses in Computer Science and related disciplines

5 Course emphasis Emphasis on problem formulation and solution methods. Learning by doing (exercises) Fewer topics, but more in depth AI concepts search knowledge representation Logic Time permitting: planning, uncertainty, natural language

6 Course organization 1. Introduction: what is AI? what are agents? 2. Problem solving: representation, search techniques, game playing 3. Knowledge representation: predicate logic, first-order logic, production rules, semantic network 4. Inference: deduction, resolution, theorem proving, soundness, completeness, prolog language 5. Planning: STRIPS, hierarchical planning 6. Learning: decision trees, version spaces

7 AI Braches Reception Vision Speech Natural Language Understanding Generation Machine Translation Common Sense reasoning Reasoning about physical objects and their relationship Robotics Planning Game Theory Mathematic Logic Engineering Fault Detection Medical diagnostic Learning Expert system

8 Useful Links

9 ?