Student Feedback
The course content is well described below. I’d say it’s interesting if you enjoy the more classical side of AI, but probably won’t be very applicable if you’re not working in that area.
Lectures
In class, Professor Inês Lynce mostly reads from the slides, which are decent and include some examples. But she answers questions well, so don’t hesitate to ask.
In practical lectures, you solve exam-style exercises.
⚠️ Be careful: Professor Lynce is not very generous with materials. Don’t expect solutions to exercises or...
The reviews below this point may be outdated. Course content, teaching methods, and requirements may have changed since then.
Course structure
The course is divided into two parts:
- The search part covers CSPs (Constraint Satisfaction Problems) and some related algorithms. This section is pretty much an extension of what’s taught in the undergrad AI course (before MEPP), specifically regarding CSPs.
- In the planning part, you learn how to define a problem so it can be solved by a planner, and study a few algorithms that determine the actions an agent should take.
Lectures
Theoretical lectures follow the course structure. In the first half of the term, the lectures are focused on search, and...