CS 461 Artificial Intelligence

Spring 2014

Course Description:

This course provides an introduction to artificial intelligence. We will start with problem-solving techniques, blind search algorithms (breadth-first, depth-first, iterative deepening, and other strategies), heuristic search algorithms (A*), and game-playing. And then we will discuss constraint satisfaction problems. We will cover knowledge representation and reasoning: syntax, semantics, and proof theory of propositional logic and first-order predicate logic, uncertainty and probabilistic reasoning. We will also discuss machine learning and natural language processing.

Moodle page of the course:

Check regularly the Moodle page of the course for lecture notes, homework assignments, and announcements.

Textbook:

• Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach (AIMA), Prentice-Hall (2010), 3rd Edition..

Course Outline:

• Introduction

• Intelligent Agents

• Solving problems by searching

• Informed search and exploration

• Adversarial search

• Constraint Satisfaction Problems

• Logical agents

• First-order logic

• Inference in first-order logic

• Knowledge representation

• Uncertainty

• Probabilistic reasoning

• Learning from observations

• Statistical learning methods

• Natural language processing

Course requirements:

• There will be three in-class quizzes (15%) with advance notice, two homework assignments (10%) involving programming and discussion, one midterm exam (40%) and one final exam (35%).

• In order to be able to take the final exam, one must obtain at least 22 points (40% of total 55) from the weighted sum of the quiz and midterm grades; else one will receive FZ.

• Check regularly the Moodle page of the course for lecture notes, homework assignments, and announcements.