This course is the first part of a two-semester introduction into the field of Artificial
Intelligence (AI). It introduces the foundations of symbolic AI, in particular:
* Agent Models as foundation of AI
* Logic Programming in Prolog
* Heuristic Search as a methdod for problem solving
* Adversarial Search (automating board games) via heuristic search
* Constraint Propagation
* Logical Languages for knowledge representation
* Inference and automated theorem proving
* Classical Planning
* Planning and Acting in the real world.
The course follows the book
[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
by Stuart Russell und Peter Norvig. We use the third edition.
The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
(some) solutions) are [here](http://kwarc.info/teaching/AI/).
The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
discussions. The instrutor and tutors try to be present to help.
### German Version (possibly out of date)
Diese Vorlesung ist der erste Teil einer zwei-semestrigen Einführung in die Künstlichen
Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen der symbolischen KI,
insbesondere
...
...
@@ -38,6 +64,6 @@ Die Kursmaterialien (z.B. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf
finden sich in [hier](http://kwarc.info/teaching/AI/).
Diskussionen finden auf dem
[FSI Forum KI-I](https://fsi.cs.fau.de/forum/144-Kuenstliche-Intelligenz) statt. Dies ist
[StudOn](https://studon.fau.de) statt. Dies ist
eine wichtige Quelle von Rat und Tat. Wir bemühen uns, auf dem Forum präsent zu sein, und
schnell auf Fragen zu antworten. Also das Forum abonnieren!
This course is the second part of a two-semester introduction into the field of Artificial
Intelligence (AI). It introducers the foundations of inference under uncertainty, machine
learning and language understanding. The course builds on and continues the course
[Artificial Intelligence I](/courses/ai1/) from the winter semester. In particular, the course
covers
* Inference under Uncertainty
* Bayesian Networks
* Rational Decision Theory (MDPs and POMDPs)
* Machine Learning and Neural Networks
* Natural Language Processing
The course follows the book
[Artificial Intelligence: A Modern Approach](https://www.pearson.com/us/higher-education/program/Russell-Artificial-Intelligence-A-Modern-Approach-3rd-Edition/PGM156683.html)
by Stuart Russell und Peter Norvig. We use the third edition.
The course materials (e.g. [Course Notes](http://kwarc.info/teaching/AI/notes.pdf) or
[Assignments](http://kwarc.info/teaching/AI/assignments.pdf), but also old exams and
(some) solutions) are [here](http://kwarc.info/teaching/AI/).
The course forum on [StudOn](https://studon.fau.de) is an important source for advice and
discussions. The instrutor and tutors try to be present to help.
### German Version (possibly out of date)
Diese Vorlesung ist der zweite Teil einer zwei-semestrigen Einführung in die Künstlichen
Intelligenz (KI). Sie beschäftigt sich mit den Grundlagen des Schliessens unter
Unsicherheit, des maschinellen Lernens und des Sprachverstehens. Der Kurs baut auf der
