Teaching · Lecture
Introduction to Artificial Intelligence
A survey of artificial intelligence through the lens of intelligent agents: from search and logic to reasoning under uncertainty, decision-making and learning.
Lecture
Winter semester
In English
When
Every winter semester at the University of Würzburg, taught in English.
Format
Weekly lectures with slides, complemented by coding assignments in which students implement the methods seen in class.
Course book
S. Russell and P. Norvig, Artificial Intelligence: A Modern Approach.
What you will learn
1 · Goal-based agents
Intelligent agents, classical search, advanced search.
2 · Reflex and model-based agents
Propositional logic, first-order logic, planning.
3 · Utility-based agents
Uncertainty quantification and probabilistic reasoning, decision theory, game theory.
4 · Learning agents
Reinforcement learning, machine learning, deep learning.
Instructors
Sebastian Griesbach
Teaching assistant
sebastian.griesbach@uni-wuerzburg.de
Mahdi Kallel
Teaching assistant
mahdi.kallel@uni-wuerzburg.de
Readings
- Course book: S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach, 3rd ed., 2010.
- C. M. Bishop. Pattern Recognition and Machine Learning. Springer, 2006.
- D. Koller and N. Friedman. Probabilistic Graphical Models: Principles and Techniques. MIT Press, 2009.
- M. Peterson. An Introduction to Decision Theory. Cambridge University Press, 2017.
- R. S. Sutton and A. G. Barto. Reinforcement Learning: An Introduction. MIT Press, 2018.