20551 Introduction to Artificial Intelligence
Credits: 4 advanced credits in Computer Science
Prerequisites: Students must fulfill all English requirements and take bibliographic instruction in the Library.
Required: Data Structures and Introduction to Algorithms (or Data Structures), Logic for Computer Science (or Mathematical Logic or Mathematics for Students of Social Sciences), Probability for Computer Science Students (or Probability Theory or Introduction to Statistics and Probability for Science Students)
The course is based on Artificial Intelligence: A Modern Approach (3rd ed.), by S. J. Russell & P. Norvig (Prentice Hall, 2010).
The field of artificial intelligence (AI) deals with building machines and writing programs to carry out sophisticated tasks that require human cognition. Research in AI today focuses on the science and engineering of designing systems to perform specific actions such as driving a car, playing chess, or planning a flight schedule. We expect these devices to perform the tasks on a high level, even higher than that which humans can achieve.
This course deals with the major AI techniques for solving a variety of types of problems, and focuses on basic topics in the field: problem solving by searching, gaming, knowledge representation and inferring new knowledge, uncertainty, planning and learning.
Topics: Introduction to artificial intelligence; Problem solving through search (uninformed search strategies, informed search strategies, heuristic functions, local search); Adversarial search – games, constraint satisfaction problems; Knowledge representation and inference using classical logic; Knowledge representation and inference under uncertainty; Planning; Learning.