Course objectives:

The course is intended to give graduate students wide spectrum about various topics in Artificial Intelligence. It is also inteneded to introduce them to various research issues and give them the necessary background for adapting AI as a research domain.

Course Contents:

1. Problem-solving
• Problem classification
• Bind Search (uninformed)
• Heuristic Search (informed)
2. Game-Playing
• Minimax Algorithm
• Negmax Algorithm
• Alpha-beta pruning algorithm
• Transposition Tables
• Horizon Effect
3. Mathematical Logic and Automated theorem-proving
1. Syntax & Semantics of a language
2. Propositional Calculus
3. Predicate Calculus:
• First order
• Second order
• Higher order
4. Inference Methods
5. Resolution strategies
• Ordering strategies
• Depth-saturation strategy
• Fewest-literals preference strategy
• Weighting strategy
• Pruning strategies
• Deleting Chaste strategy
• Deleting Tautologies
• Deleting subsumed clauses
• Restriction strategies
• Set of support strategy
• Negative resolution strategy
• Negative hyper-resolution strategy
• Positive resolution strategy
• Positive hyper-resolution strategy
• Ancestory filtered-form strategy
• Linear input-form strategy
• Unit resolution strategy
• Handling Equality Literal
• Demodulation
• Paramodulation
4. Expert Systems
• Structure of Expert System
• Components of Expert system
• Need for expert systems
• Types of Expert systems
• Backward chaining
• Forward chaining
• User interface role in expert system
5. Probabilistic Reasoning
• Reasoning using probabilities
• Necessity & Sufficiency measures
6. Genetic Algorithms

Title: Formal Concepts in Artificial Intelligence: Fundamentals
Author: Rajjan Shinghal

1. Artificial Intelligence: A Modern Approach by Stuart Russell and Peter Norving, Prentice-Hall
2. How Computer Play Chess, David Levy and Monty Newborn, Computer Science Press

• Assignments %20
• Assignment 1    Tree Search Techniques %10
• Assignment 2    Automated Theorem Proving %10
• Midterm1 %15          March 4th , 2000
• Grades
• Midterm2 %15          April 8th, 2000
• Grades
• Final Exam %30

• Search in State Space Representations
• Some Search Algorithms
• MiniMax with Alpha-Beta Pruning
• Constraint Satisfaction Problems
• Introduction to Genetic Algorithms
• Topics in Genetic Algorithms