Master in Information and Computer Sciences

Intelligent Agents I
Module:Module 2.7, Semester 2
Objective: The objective of this course is to introduce students to knowledge representation and reasoning methods for intelligent agent systems.
Course learning outcomes: * Explain the nature and roles of different formal theories used for individual reasoning and autonomous agents, such as various modal logics, belief change formalisms, or methods for uncertainty management
* Define and apply the basic concepts of one or two non-classical logics (e.g. modal logic and default logics), notably their semantics and proof calculi
* Model intelligent systems using non-classical logics
* Explain the philosophical foundations of individual reasoning.

Description: The course has 4 parts:
1. Modal logics for agent reasoning
2. Conditional logic
3. Natural language semantics & non-monotonic logic
4. Formal argumentation
Language: English
Lecturer: VAN DER TORRE Leon
Rating: Final exam 65%; Homework 35%.