Artificial Intelligence 1[go to overview]
The course "Artificial Intelligence 1" provides an overview on basic approaches of artificial intelligence within the areas of search, planning, knowledge representation, reasoning, and multi agent systems. The aim of this course is to teach foundational principles of symbolic AI approaches, its connections to logic, and basic formalisation aspects. The theoretical concepts taught in the lecture will be accompanied by practical programming exercises with Prolog. The contents of this course are as follows
- Classical Logics and Prolog
- Classical logics
- Search and Automatic Planning
- Uninformed search
- Informed search
- Situation calculus and STRIPS
- Knowledge Representation and Reasoning
- Default logic
- Answer set programming
- Formal argumentation
- Agents and Multi Agent Systems
- Agent models
- Multi agent logics
- Summary and Conclusion
- Mondays 10:15-11:45 in E.314
- No lecture on May 21 (Pfingsten)
- Thursdays 14:15-15:45 in F.314
- No tutorials on April 12, May 10, May 24, and May 31 (First lecture week, Christi Himmelfahrt, Pfingsten, Fronleichnam)
- Please register in Teams until April 18
- Assignments are uploaded using SVN. You need a SVN client to upload your assignments.
- Organisational Introduction
- 1. Introduction
- 2. Classical logics and Prolog
- 3. Search and automatic planning
- 4. Knowledge Representation and Reasoning
- 5. Agents and Multi Agent Systems
- 6. Summary and Conclusion
- Assignment 1 (due: 20.04.18)
- Assignment 2 (due: 27.04.18)
- Assignment 3 (due 04.05.18) (updated on 03.05)
- Assignment 4 (due 18.05.18) (updated on 13.05, fixed typos)
- Assignment 5 (due 08.06.18) (updated on 28.05, new submission date)
- Assignment 6 (due 15.06.18)
- Assignment 7 (due 22.06.18)
- Assignment 8 (due 29.06.18)
- Assignment 9 (due 06.07.18) (updated on 05.07)
- Slides of the lecture "Logik für Informatiker" SoSe 2017 (in German)
- Material from "Logic for Computer Scientiests" by Uli Furbach (in English)
Please acknowledge the following guidelines to obtain the credits for this course:
- In order to obtain the credits of this course (6 ECTS), you have to obtain admission to take part in the exam and pass the exam.
- Admission to the exam is granted to all students who achieve 60% of the score obtainable in the exercises of the tutorials.
- Active participation in the tutorials is expected.
- Obligation to register for the exam
- There is an obligation to register for the exam.
- If someone is not correctly registered for the exam before the end of the corresponding deadline, he or she cannot participate in the exam.
- If someone is registered for the exam but does not show up, he or she will fail the exam.
- If you fail the (written) exam you have to do a retake within the next 6 months; this second (or third) exam is orally and has to be scheduled with the lecturer via mail.
The following textbooks are recommended:
- Stuart Russell, Peter Norvig: Artificial Intelligence: A Modern Approach
Third Edition, Prentice Hall, 2010
- Christoph Beierle, Gabriele Kern-Isberner: Methoden wissensbasierter Systeme
Vierte Auflage, Vieweg+Teubner, 2008 (in German)
- Ronald Brachman, Hector Levesque: Knowledge Representation and Reasoning
First Edition, Morgan Kaufmann Series, 2004
- Gerhard Weiss (Editor): Multiagent Systems
Second Edition, MIT Press, 2013