CS 461 Artificial Intelligence

Spring 2013

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, two homework assignments involving programming and discussion, one midterm exam and one final exam.

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