Seminar Logic-Based Knowledge Representation

Seminar Logic-Based Knowledge Representation

Course with SWS 0/2/0 (lecture/exercise/practical) in SS 2025

Lecturer

• Sarah Alice Gaggl

SWS

• 0/2/0

Modules

• INF-AQUA
• INF-PM-FOR
• INF-04-HS
• INF-D-940
• CMS-SEM-A

Examination method

• Term paper
• Seminar presentation
• according to module description

• Information
• Literature
• Dates and Materials

Course Description

This seminar intends to introduce to selected topics of an active research areas in the field of knowledge representation by analyzing introductory literature as well as research papers. In particular, we will focus on the topic Inductive Logic Programming.

Prerequisites

Students are expected to be familiar with logic programming.

Seminar Plan

The seminar will take place on Mondays 16:40 – 18:10 in room APB E005, on the dates indicated in the schedule. The topics will be selected in the first session on April 14.

1. Inductive Learning of Answer Set Programs https://www.doc.ic.ac.uk/~ml1909/ILASP_Paper.pdf
2. Learning efficient logic programs https://link.springer.com/article/10.1007/s10994-018-5712-6
3. Learning higher-order logic programs https://link.springer.com/article/10.1007/s10994-019-05862-7
4. Learning Large Logic Programs By Going Beyond Entailment https://www.ijcai.org/proceedings/2020/0287.pdf
5. The Game of Bridge: A Challenge for ILP https://link.springer.com/chapter/10.1007/978-3-319-99960-9_5
6. Learning Strategies of Inductive Logic Programming Using Reinforcement Learning https://link.springer.com/chapter/10.1007/978-3-031-49299-0_4
7. What Do Counterfactuals Say About the World? Reconstructing Probabilistic Logic Programs from Answers to “What If?” Queries https://link.springer.com/chapter/10.1007/978-3-031-49299-0_7
8. Lifting Symmetry Breaking Constraints with Inductive Logic Programming http://lr2020.iit.demokritos.gr/online/Tarzariol_Alice_Journal.pdf
9. Inductive Learning of Answer Set Programs for Autonomous Surgical Task Planning - Application to a Training Task for Surgeons http://lr2020.iit.demokritos.gr/online/meli.pdf
10. Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP https://link.springer.com/article/10.1007/s10994-018-5707-3

already chosen topics

1. Inductive Learning of Answer Set Programs https://www.doc.ic.ac.uk/~ml1909/ILASP_Paper.pdf

2. Learning efficient logic programs https://link.springer.com/article/10.1007/s10994-018-5712-6

4. Learning Large Logic Programs By Going Beyond Entailment https://www.ijcai.org/proceedings/2020/0287.pdf

5. The Game of Bridge: A Challenge for ILP https://link.springer.com/chapter/10.1007/978-3-319-99960-9_5

6. Learning Strategies of Inductive Logic Programming Using Reinforcement Learning https://link.springer.com/chapter/10.1007/978-3-031-49299-0_4

7. What Do Counterfactuals Say About the World? Reconstructing Probabilistic Logic Programs from Answers to “What If?” Queries https://link.springer.com/chapter/10.1007/978-3-031-49299-0_7

8. Lifting Symmetry Breaking Constraints with Inductive Logic Programming http://lr2020.iit.demokritos.gr/online/Tarzariol_Alice_Journal.pdf

9. Inductive Learning of Answer Set Programs for Autonomous Surgical Task Planning - Application to a Training Task for Surgeons http://lr2020.iit.demokritos.gr/online/meli.pdf

10. Ultra-Strong Machine Learning: comprehensibility of programs learned with ILP https://link.springer.com/article/10.1007/s10994-018-5707-3

Examination

Students are expected to (1) give a talk on one of the topics listed above and (2) to write a term paper and (3) participate in the peer-reviewing process of the term papers from this seminar. The exact requirements for the talks and term papers will be discussed in the seminar.

Inductive Logic Programming At 30: A New Introduction, Andrew Cropper and Sebastijan Dumančić https://www.jair.org/index.php/jair/article/view/13507

Subscribe to events of this course (icalendar)

Seminar

Introduction - Topic selection

DS6, April 14, 2025 in APB E005

Calendar