Knowledge Representation and Reasoning

Graduate

This course provides and overview on the core of Symbolic AI, covering key topics such as Propositional and First-Order Logic, Non- Monotonic Logics, and techniques for Reasoning under Uncertainty: Probabilistic and possibilistic logics. Students will explore advanced methods like Bayesian Networks and their applications in decision-making under uncertainty, as well as planning techniques. The course also covers Case-Based Reasoning for problem solving.