|
Responsible Instructor |
|
|
Contact Hours / Week x/x/x/x |
2/2/0/0 college
1/1/0/0 instructie
Pract.
|
|
Education Period |
|
|
Start Education |
|
|
Exam Period |
|
|
Course Language |
|
|
Expected prior knowledge |
Computer science experience and knowledge at Bachelor level or similar, including in particular knowledge of algorithms (e.g. search algorithms), logic (IN1305-I), and probability theory (WI2105IN).
|
|
Course Contents |
Artificial Intelligence techniques for building rational agents and decision support systems are presented. Various techniques needed are discussed, including automated reasoning, action selection and planning, and learning. In addition, various models needed to design and build such systems are discussed, including cognitive architectures, mental models, decision making, and strategic interaction.
|
|
Study Goals |
After successful completion of the course:
- Students have a general overview of artificial intelligence
- Students are able to apply various artificial intelligence techniques
- Students are able to model knowledge and preferences using and knowledge representation languages.
- Students are able to design and implement intelligent agents for complex decision making problems.
|
|
Education Method |
Lectures, tutorials, lab work
|
|
Literature and Study Materials |
Stuart J. Russel and Peter Norvig (2003). Artificial Intelligence: A Modern Approach. Prentice-Hall. ISBN-13: 978-0131038059 + additional handouts.
|
|
Assessment |
Written exam, homework assignments, and assignments.
|
|
Remarks |
40 hrs of lab work
|