Logic, Knowledge Representation and Probabilities
➜ other AI courses
Introduction
The course is organized around weekly topics. For each topic, there is a lecture followed by a lab session. For the lab sessions, students connect to the relevant page on the
web site. They will find some text to read, small open questions and small programming exercises that they can try on their own machine (or on the machines provided in the lab room). Answers are recorded and contribute to the final grade. For most questions, a possible solution becomes accessible after answering. Lab sessions can be completed during until just before the next lecture (see dates in the
table below). Answers are no longer recorded beyond the deadline indicated for each topic, which means students will need to work on a weekly basis.
Exam
There will be an exam (on paper, no documents, no turned-on device, 90 minutes) at the end of the course, contributing to ~70% of the final grade. It will consist in small short and independent exercises about Prolog, logic and other topics. No documents, no functionning devices.
Labs
Lab sessions are in rooms equipped with machines, but your are welcome to use your own. We will be working with the free Prolog Interpreter
SWI-Prolog.
Don’t hesitate to ask questions to teachers during the labs, they are there FOR YOU.
Answers to lab exercises will be read and evaluated. They will contribute to the final grade (~30%).
Topics
Gabriel Poesia, Kanishk Gandhi, Eric Zelikman and Noah D. Goodman,
Certified Deductive Reasoning with Language Models,
Arxiv 2023.
Chiang, T. (2023). ChatGPT is a blurry JPEG of the Web.
Annals of Technology - The New Yorker,
Feb.
Evans, J. & Rzhetsky, A. (2010).
Machine science.
Science,
329 (5990), 399-400.
Nils Holzenberger
← Home pageApril 2025
