Undergraduate Program - Department of Electrical and Computer Engineering
ARTIFICIAL INTELLIGENCE
Description
The course aims to present the fundamental concepts and techniques of Artificial Intelligence and to highlight the philosophical problems that arise in the course of developing or using intelligent systems. The course addresses these issues from the perspective of intelligent agents, i.e., from a distributed artificial intelligence view, as this has become mainstream since 1995, and it brings together all technical and philosophical issues of interest. Τhe main areas covered include:
- Search for problem solving
- Knowledge Representation
- Planning
- Decision theory
- Decisions under uncertainty
- Machine learning
Subject area
Applications and Foundations of Computer Science
Learning Outcomes
Upon successful completion of the course, students
- Know the broader historical, philosophical and scientific context in which the development of intelligent systems is examined.
- Know the basic algorithms for solving problems through search, the ways in which knowledge can be represented with emphasis on symbolic (logic) representations, the main algorithms employed in planning, decision theory principles, the main approaches to reasoning under uncertainty and the main concepts and algorithms for machine learning.
- Understand and assess critically various algorithms and symbolic representations and appreciate their complexity.
- Apply the basic techniques and algorithms to problems.