Lecture: A Model-Oriented Approach for Lifting Symmetry-Breaking Constraints i...

Master data
Title: A Model-Oriented Approach for Lifting Symmetry-Breaking Constraints in Answer Set Programming
Description:

Writing correct models for combinatorial problems is relatively straightforward; however, they must be efficient to be usable with instances producing many solution candidates. In this work, we aim to automatically generalise the discarding of symmetric solutions of Answer Set Programming instances, improving the efficiency of the programs with first-order constraints derived from propositional symmetry-breaking constraints.
Keywords: Search and Optimization, Knowledge Representation and Reasoning, Machine Learning
Type: Registered lecture
Homepage: https://www.ijcai.org/proceedings/2022/840
Event: IJCAI-ECAI 2022, THE 31ST INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE (Wien)
Date: 25.07.2022
lecture status: stattgefunden (Präsenz)

Participants
Alice Tarzariol
Alice.Tarzariol@aau.at
Institut für Artificial Intelligence und Cybersecurity
Research activities
To visiting card
(internal)
  • Speaker
  • Author

Assignment
Organisation Address
Fakultät für Technische Wissenschaften
  Institut für Artificial Intelligence und Cybersecurity
Universitätsstr. 65-67
A-9020 Klagenfurt
Austria
  -993705
   aics-office@aau.at
https://www.aau.at/en/aics/
To organisation
Universitätsstr. 65-67
AT - A-9020  Klagenfurt

Categorisation
Subject areas
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Focus of lecture
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
Group of participants
  • Mainly international
Published?
  • Yes
working groups
  • Adaptive und Vernetzte Produktionssysteme

Cooperations
No partner organisations selected