This course provides a comprehensive view of Artificial Intelligence, by selecting for study some of the main topics of the discipline: search, knowledge representation and resoning, planning and learning. The several approaches and paradigms are illustrated in the several course projects.
These subjects are treated in sufficient detail that allows students to solve toy problems as well as understand the difficulties of real problem instances. In the lab classes students will develop selected programming projects where the learnt techniques can be applied to solve some problems, both by implementing small prototypes and by modeling the problems in existing tools.
- Informed search state-spaces.
- Local search.
- Adversarial search.
- Logic programming.
- Probabilistic logic.
- Machine learning.