| Time | Details |
|---|---|
| 12:30 | Welcome |
| 12:45-13:45 | Invited Talk by Mario Alviano |
| 13:45-14:00 | Short Break |
| 14:00-14:15 | Two-sorted Dynamic Here-and-There Arvid Becker, Torsten Schaub, Pedro Cabalar and Martin Dieguez |
| 14:15-14:30 | Temporal Here and There with Constraints Pedro Cabalar, Martín Diéguez, François Olivier, Torsten Schaub and Igor Stéphan |
| 14:30-14:45 | Here and There with Constraints for Spatial Reasoning François Olivier and Carl Schultz |
| 14:45-15:00 | Past-present temporal programs over finite traces Pedro Cabalar, Martín Diéguez, François Laferriere and Torsten Schaub |
| 15:00-15:30 | Coffee Break |
| 15:30-15:45 |
Capturing (Optimal) Relaxed Plans with Stable and Supported Models of Logic Programs Masood Feyzbakhsh Rankooh and Tomi Janhunen |
| 15:45-16:00 |
Modelling Curriculum-Based Course Timetabling of University of Potsdam Sebastian Schellhorn |
| 16:00-16:15 |
Reasoning about Study Regulations in Answer Set Programming Susana Hahn, Cedric Martens, Amadé Nemes, Henry Otunuya, Javier Romero, Torsten Schaub and Sebastian Schellhorn |
| 16:15-16:30 |
Enhancing Temporal Planning by Sequential Macro-actions Marco De Bortoli, Lukáš Chrpa, Martin Gebser and Gerald Steinbauer-Wagner |
| 16:30-17:00 | Coffee Break |
| 17:00-17:15 |
Hybrid ASP-based multi-objective scheduling of semiconductor manufacturing processes Mohammed El-Kholany, Ramsha Ali and Martin Gebser |
| 17:15-17:30 |
Improving the Sum-of-Cost Computation for Multi-Agent Pathfinding in Answer Set Programming Klaus Strauch, Roland Kaminski and Jiří Švancara |
| 17:30-17:45 |
Design Space Exploration at the Electronic System Level Luise Müller and Christian Haubelt |
| 17:45-18:00 |
Pruning Redundancy in Answer Set Optimization Applied to Preventive Maintenance Scheduling Anssi Yli-Jyrä, Masood Feyzbakhsh Rankooh and Tomi Janhunen |
| 18:30-22:00 | Social Program: Stellwerk Golm |
| Time | Title |
|---|---|
| 09:00-09:15 |
Clinguin: Building User Interfaces in ASP Susana Hahn |
| 09:15-09:30 |
OWL2QL Meta-reasoning Using ASP-based Hybrid Knowledge Bases Haya Majid Qureshi and Wolfgang Faber |
| 09:30-09:45 |
Dynamic Aggregates in Expressive ASP Heuristics for Configuration Problems Richard Comploi-Taupe, Gerhard Friedrich and Tilman Niestroj |
| 09:45-10:00 |
Neuro-Symbolic Visual Graph Question Answering with LLMs for Language Parsing Jakob Bauer, Thomas Eiter, Nelson Higuera and Johannes Oetsch |
| 10:00-10:30 | Coffee Break |
| 10:30-10:45 |
On Establishing Robust Consistency in Answer Set Programs Andre Thevapalan and Gabriele Kern-Isberner |
| 10:45-11:00 |
clintest: Efficient off-the-shelf unit testing for clingo programs Tobias Stolzmann |
| 10:45-11:00 |
On the ASP Grounding Bottleneck Over Aggregates: Efficiently Grounding via Rewriting & Solving Alexander Beiser, Markus Hecher, Kaan Unalan and Stefan Woltran |
| 11:15-11:30 | Small Break |
| 11:30-12:30 | Invited Talk by Tomi Janhunen |
Answer Set Programming (ASP) is an amazing language and I love it. Thanks to ASP I can save a considerable amount of development time when I am asked to address some combinatorial and optimization problems. Nonetheless, I can see that ASP comes with some severe lacks preventing its broad adoption in the wild. Truth is that what ASP practitioners find "simple" to use can be challenging to digest for a novice. And while learning a new language is expected to be challenging, there is one specific lack of ASP that undermines the interest of novices and limits the potential of the language: ASP lacks code isolation mechanisms. Writing an ASP program requires a considerable mental effort, as compatibility of any new rule must be (mentally) verified with all previously written rules. The situation does not improve if one tries to take advantage of the work done by expert programmers, as anyhow a full understanding of third party code is eventually required. There is no space for building libraries to share and decentralize code of common usage. Automatic testing is also limited, as the lack of isolation prevents the enforcement of invariants. Putting myself in the shoes of a novice, I see that they are asked to take roughly the same path I walked around 20 years ago, with the promise of encountering something interesting at the end of the journey. But computer programming is not the same of 20 years ago, and walking that path knowing the existence of amazing frameworks and low-code technologies is in full honestly a torture. What can we do to make ASP more attractive, without overturning the basic language and engines?
In answer set programming (ASP), solutions to search problems of interest are captured with answer sets whose efficient computation is of utmost importance. To this end, translation-based ASP provides one viable implementation strategy: the idea is (i) to translate logic programs into other KR formalisms such as Boolean satisfiability, SAT modulo theories, and mixed-integer programming; and (ii) to harness the respective solver technology for the computation of answer sets. Many of the existing translations are based on Clark's completion, further exploiting level rankings to capture the minimality of answer sets and default negation properly. In this invited talk, I recall aggregate-based extensions of ASP as well as their existing implementations under translation-based ASP, mainly based on rewriting into normal rules. Then, I present a recent generalization of level ranking constraints, enabling their incorporation in the context of monotone and convex aggregates in such a way that the structure of aggregates can be preserved. This offers a uniform basis for incorporation of aggregates into translation-based ASP and opens up new possibilities for the implementation of translators and solver pipelines in practice.