8 Search Results for "Seipel, Dietmar"

Document
DOI: 10.4230/LIPIcs.CP.2025.33
Constraint-Based In-Station Train Dispatching

Authors: Andreas Schutt, Matteo Cardellini, Jip J. Dekker, Daniel Harabor, Marco Maratea, and Mauro Vallati

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
In-station dispatching is the problem of planning the movements of scheduled trains inside a railway station. Effective solutions for in-station dispatching are important for maximising the utilisation of railway infrastructure and for mitigating the impact of incidents and delays in the broader network. In this paper, we explore a constraint-based approach to perform in-station train dispatching. Our extensive empirical analysis of multiple modelling, search strategy, and solver choices, performed over synthetically generated, yet realistic, data, shows that our method outperforms the existing planning-based state-of-the-art approach. In addition, we present different optimisation criteria, which can be effortless defined thanks to the constraint-based approach.
Cite as

Andreas Schutt, Matteo Cardellini, Jip J. Dekker, Daniel Harabor, Marco Maratea, and Mauro Vallati. Constraint-Based In-Station Train Dispatching. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 33:1-33:24, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{schutt_et_al:LIPIcs.CP.2025.33,
  author =	{Schutt, Andreas and Cardellini, Matteo and Dekker, Jip J. and Harabor, Daniel and Maratea, Marco and Vallati, Mauro},
  title =	{{Constraint-Based In-Station Train Dispatching}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{33:1--33:24},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.33},
  URN =		{urn:nbn:de:0030-drops-238941},
  doi =		{10.4230/LIPIcs.CP.2025.33},
  annote =	{Keywords: in-station train dispatching, train scheduling, railway scheduling, constraint programming, mixed-integer programming}
}
Document
DOI: 10.4230/LIPIcs.CP.2025.17
Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks

Authors: Mohimenul Kabir, Van-Giang Trinh, Samuel Pastva, and Kuldeep S Meel

Published in: LIPIcs, Volume 340, 31st International Conference on Principles and Practice of Constraint Programming (CP 2025)

Abstract
Boolean Networks (BNs) serve as a fundamental modeling framework for capturing complex dynamical systems across various domains, including systems biology, computational logic, and artificial intelligence. A crucial property of BNs is the presence of trap spaces - subspaces of the state space that, once entered, cannot be exited. Minimal trap spaces, in particular, play a significant role in analyzing the long-term behavior of BNs, making their efficient enumeration and counting essential. The fixed points in BNs are a special case of minimal trap spaces. In this work, we formulate several meaningful counting problems related to minimal trap spaces and fixed points in BNs. These problems provide valuable insights both within BN theory (e.g., in probabilistic reasoning and dynamical analysis) and in broader application areas, including systems biology, abstract argumentation, and logic programming. To address these computational challenges, we propose novel methods based on approximate answer set counting, leveraging techniques from answer set programming. Our approach efficiently approximates the number of minimal trap spaces and the number of fixed points without requiring exhaustive enumeration, making it particularly well-suited for large-scale BNs. Our experimental evaluation on an extensive and diverse set of benchmark instances shows that our methods significantly improve the feasibility of counting minimal trap spaces and fixed points, paving the way for new applications in BN analysis and beyond.
Cite as

Mohimenul Kabir, Van-Giang Trinh, Samuel Pastva, and Kuldeep S Meel. Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks. In 31st International Conference on Principles and Practice of Constraint Programming (CP 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 340, pp. 17:1-17:26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{kabir_et_al:LIPIcs.CP.2025.17,
  author =	{Kabir, Mohimenul and Trinh, Van-Giang and Pastva, Samuel and Meel, Kuldeep S},
  title =	{{Scalable Counting of Minimal Trap Spaces and Fixed Points in Boolean Networks}},
  booktitle =	{31st International Conference on Principles and Practice of Constraint Programming (CP 2025)},
  pages =	{17:1--17:26},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-380-5},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{340},
  editor =	{de la Banda, Maria Garcia},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.CP.2025.17},
  URN =		{urn:nbn:de:0030-drops-238780},
  doi =		{10.4230/LIPIcs.CP.2025.17},
  annote =	{Keywords: Computational systems biology, Boolean network, Fixed point, Trap space, Answer set counting, Projected counting, Abstract argumentation, Logic programming}
}
Document
DOI: 10.4230/OASIcs.SLATE.2025.3
Elements for Weighted Answer-Set Programming

Authors: Francisco Coelho, Bruno Dinis, Dietmar Seipel, and Salvador Abreu

Published in: OASIcs, Volume 135, 14th Symposium on Languages, Applications and Technologies (SLATE 2025)

Abstract
Logic programs, more specifically, answer-set programs, can be annotated with probabilities on facts to express uncertainty. We address the problem of propagating weight annotations on facts (e.g. probabilities) of an answer-set program to its stable models, and from there to events (defined as sets of atoms) in a dataset over the program’s domain. We propose a novel approach which is algebraic in the sense that it relies on an equivalence relation over the set of events. Uncertainty is then described as polynomial expressions over variables. We propagate the weight function in the space of models and events, rather than doing so within the syntax of the program. As evidence that our approach is sound, we show that certain facts behave as expected. Our approach allows us to investigate weight annotated programs and to determine how suitable a given one is for modeling a given dataset containing events. It’s core is illustrated by a running example and the encoding of a Bayesian network.
Cite as

Francisco Coelho, Bruno Dinis, Dietmar Seipel, and Salvador Abreu. Elements for Weighted Answer-Set Programming. In 14th Symposium on Languages, Applications and Technologies (SLATE 2025). Open Access Series in Informatics (OASIcs), Volume 135, pp. 3:1-3:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{coelho_et_al:OASIcs.SLATE.2025.3,
  author =	{Coelho, Francisco and Dinis, Bruno and Seipel, Dietmar and Abreu, Salvador},
  title =	{{Elements for Weighted Answer-Set Programming}},
  booktitle =	{14th Symposium on Languages, Applications and Technologies (SLATE 2025)},
  pages =	{3:1--3:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-387-4},
  ISSN =	{2190-6807},
  year =	{2025},
  volume =	{135},
  editor =	{Baptista, Jorge and Barateiro, Jos\'{e}},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2025.3},
  URN =		{urn:nbn:de:0030-drops-236836},
  doi =		{10.4230/OASIcs.SLATE.2025.3},
  annote =	{Keywords: Answer-Set Programming, Stable Models, Probabilistic Logic Programming}
}
Document
DOI: 10.4230/OASIcs.SLATE.2023.6
Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge

Authors: Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu

Published in: OASIcs, Volume 113, 12th Symposium on Languages, Applications and Technologies (SLATE 2023)

Abstract
We are extending the keyword-based query interface DdQl for relational databases which is based on contextual background knowledge such as suitable join conditions and which was proposed in [{Dietmar Seipel, 2021]. In the previous paper, join conditions were extracted from existing referential integrity (foreign key) constraints of the database schema, or they could be learned from other, previous database queries. In this paper, we describe a speech-to-text component for entering the query keywords based on the system Whisper. Keywords, which have been recognized wrongly by Whisper can be corrected to similarly sounding words. Again, the context of the database schema can help here. For users with a limited knowledge of the schema and the contents of the database, the approach of DdQl can help to provide useful suggestions for query implementations in Sql or Datalog, from which the user can choose one. Our tool DdQl can be run in a docker image; it yields the possible queries in Sql and a special domain specific rule language that extends Datalog. The Datalog variant allows for additional user-defined aggregation functions which are not possible in Sql.
Cite as

Dietmar Seipel, Benjamin Förster, Magnus Liebl, Marcel Waleska, and Salvador Abreu. Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge. In 12th Symposium on Languages, Applications and Technologies (SLATE 2023). Open Access Series in Informatics (OASIcs), Volume 113, pp. 6:1-6:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2023)

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@InProceedings{seipel_et_al:OASIcs.SLATE.2023.6,
  author =	{Seipel, Dietmar and F\"{o}rster, Benjamin and Liebl, Magnus and Waleska, Marcel and Abreu, Salvador},
  title =	{{Querying Relational Databases with Speech-Recognition Driven by Contextual Knowledge}},
  booktitle =	{12th Symposium on Languages, Applications and Technologies (SLATE 2023)},
  pages =	{6:1--6:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-291-4},
  ISSN =	{2190-6807},
  year =	{2023},
  volume =	{113},
  editor =	{Sim\~{o}es, Alberto and Ber\'{o}n, Mario Marcelo and Portela, Filipe},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2023.6},
  URN =		{urn:nbn:de:0030-drops-185202},
  doi =		{10.4230/OASIcs.SLATE.2023.6},
  annote =	{Keywords: Knowledge Bases, Natural Language Interface, Logic Programming, Definite Clause Grammars, Referential Integrity Constraints, Speech-to-Text}
}
Document
DOI: 10.4230/OASIcs.SLATE.2021.16
Intelligent Query Answering with Contextual Knowledge for Relational Databases

Authors: Dietmar Seipel, Daniel Weidner, and Salvador Abreu

Published in: OASIcs, Volume 94, 10th Symposium on Languages, Applications and Technologies (SLATE 2021)

Abstract
We are proposing a keyword-based query interface for knowledge bases - including relational or deductive databases - based on contextual background knowledge such as suitable join conditions or synonyms. Join conditions could be extracted from existing referential integrity (foreign key) constaints of the database schema. They could also be learned from other, previous database queries, if the database schema does not contain foreign key constraints. Given a textual representation - a word list - of a query to a relational database, one may parse the list into a structured term. The intelligent and cooperative part of our approach is to hypothesize the semantics of the word list and to find suitable links between the concepts mentioned in the query using contextual knowledge, more precisely join conditions between the database tables. We use a knowledge-based parser based on an extension of Definite Clause Grammars (Dcg) that are interweaved with calls to the database schema to suitably annotate the tokens as table names, table attributes, attribute values or relationships linking tables. Our tool DdQl yields the possible queries in a special domain specific rule language that extends Datalog, from which the user can choose one.
Cite as

Dietmar Seipel, Daniel Weidner, and Salvador Abreu. Intelligent Query Answering with Contextual Knowledge for Relational Databases. In 10th Symposium on Languages, Applications and Technologies (SLATE 2021). Open Access Series in Informatics (OASIcs), Volume 94, pp. 16:1-16:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021)

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@InProceedings{seipel_et_al:OASIcs.SLATE.2021.16,
  author =	{Seipel, Dietmar and Weidner, Daniel and Abreu, Salvador},
  title =	{{Intelligent Query Answering with Contextual Knowledge for Relational Databases}},
  booktitle =	{10th Symposium on Languages, Applications and Technologies (SLATE 2021)},
  pages =	{16:1--16:15},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-202-0},
  ISSN =	{2190-6807},
  year =	{2021},
  volume =	{94},
  editor =	{Queir\'{o}s, Ricardo and Pinto, M\'{a}rio and Sim\~{o}es, Alberto and Portela, Filipe and Pereira, Maria Jo\~{a}o},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2021.16},
  URN =		{urn:nbn:de:0030-drops-144330},
  doi =		{10.4230/OASIcs.SLATE.2021.16},
  annote =	{Keywords: Knowledge Bases, Natural Language Interface, Logic Programming, Definite Clause Grammars, Referential Integrity Constraints}
}
Document
DOI: 10.4230/OASIcs.SLATE.2019.7
Definite Clause Grammars with Parse Trees: Extension for Prolog

Authors: Falco Nogatz, Dietmar Seipel, and Salvador Abreu

Published in: OASIcs, Volume 74, 8th Symposium on Languages, Applications and Technologies (SLATE 2019)

Abstract
Definite Clause Grammars (DCGs) are a convenient way to specify possibly non-context-free grammars for natural and formal languages. They can be used to progressively build a parse tree as grammar rules are applied by providing an extra argument in the DCG rule’s head. In the simplest way, this is a structure that contains the name of the used nonterminal. This extension of a DCG has been proposed for natural language processing in the past and can be done automatically in Prolog using term expansion. We extend this approach by a meta-nonterminal to specify optional and sequences of nonterminals, as these structures are common in grammars for formal, domain-specific languages. We specify a term expansion that represents these sequences as lists while preserving the grammar’s ability to be used both for parsing and serialising, i.e. to create a parse tree by a given source code and vice-versa. We show that this mechanism can be used to lift grammars specified in extended Backus-Naur form (EBNF) to generate parse trees. As a case study, we present a parser for the Prolog programming language itself based only on the grammars given in the ISO Prolog standard which produces corresponding parse trees.
Cite as

Falco Nogatz, Dietmar Seipel, and Salvador Abreu. Definite Clause Grammars with Parse Trees: Extension for Prolog. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 7:1-7:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{nogatz_et_al:OASIcs.SLATE.2019.7,
  author =	{Nogatz, Falco and Seipel, Dietmar and Abreu, Salvador},
  title =	{{Definite Clause Grammars with Parse Trees: Extension for Prolog}},
  booktitle =	{8th Symposium on Languages, Applications and Technologies (SLATE 2019)},
  pages =	{7:1--7:14},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-114-6},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{74},
  editor =	{Rodrigues, Ricardo and Janou\v{s}ek, Jan and Ferreira, Lu{\'\i}s and Coheur, Lu{\'\i}sa and Batista, Fernando and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2019.7},
  URN =		{urn:nbn:de:0030-drops-108743},
  doi =		{10.4230/OASIcs.SLATE.2019.7},
  annote =	{Keywords: Definite Clause Grammar, Prolog, Term Expansion, Parse Tree, EBNF}
}
Document
DOI: 10.4230/OASIcs.SLATE.2019.17
Alexa, How Can I Reason with Prolog?

Authors: Falco Nogatz, Julia Kübert, Dietmar Seipel, and Salvador Abreu

Published in: OASIcs, Volume 74, 8th Symposium on Languages, Applications and Technologies (SLATE 2019)

Abstract
As with Amazon’s Echo and its conversational agent Alexa, smart voice-controlled devices become ever more present in daily life, and many different applications can be integrated into this platform. In this paper, we present a framework that eases the development of skills in Prolog. As Prolog has a long history in natural language processing, we may integrate well-established techniques, such as reasoning about knowledge with Attempto Controlled English, instead of depending on example phrases and pre-defined slots.
Cite as

Falco Nogatz, Julia Kübert, Dietmar Seipel, and Salvador Abreu. Alexa, How Can I Reason with Prolog?. In 8th Symposium on Languages, Applications and Technologies (SLATE 2019). Open Access Series in Informatics (OASIcs), Volume 74, pp. 17:1-17:9, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)

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@InProceedings{nogatz_et_al:OASIcs.SLATE.2019.17,
  author =	{Nogatz, Falco and K\"{u}bert, Julia and Seipel, Dietmar and Abreu, Salvador},
  title =	{{Alexa, How Can I Reason with Prolog?}},
  booktitle =	{8th Symposium on Languages, Applications and Technologies (SLATE 2019)},
  pages =	{17:1--17:9},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-114-6},
  ISSN =	{2190-6807},
  year =	{2019},
  volume =	{74},
  editor =	{Rodrigues, Ricardo and Janou\v{s}ek, Jan and Ferreira, Lu{\'\i}s and Coheur, Lu{\'\i}sa and Batista, Fernando and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2019.17},
  URN =		{urn:nbn:de:0030-drops-108841},
  doi =		{10.4230/OASIcs.SLATE.2019.17},
  annote =	{Keywords: Prolog, Attempto Controlled English, Voice-Controlled Agents, Controlled Natural Language}
}
Document
DOI: 10.4230/OASIcs.SLATE.2016.7
Declarative Rules for Annotated Expert Knowledge in Change Management

Authors: Dietmar Seipel, Rüdiger von der Weth, Salvador Abreu, Falco Nogatz, and Alexander Werner

Published in: OASIcs, Volume 51, 5th Symposium on Languages, Applications and Technologies (SLATE'16) (2016)

Abstract
In this paper, we use declarative and domain-specific languages for representing expert knowledge in the field of change management in organisational psychology. Expert rules obtained in practical case studies are represented as declarative rules in a deductive database. The expert rules are annotated by information describing their provenance and confidence. Additional provenance information for the whole - or parts of the - rule base can be given by ontologies. Deductive databases allow for declaratively defining the semantics of the expert knowledge with rules; the evaluation of the rules can be optimised and the inference mechanisms could be changed, since they are specified in an abstract way. As the logical syntax of rules had been a problem in previous applications of deductive databases, we use specially designed domain-specific languages to make the rule syntax easier for non-programmers. The semantics of the whole knowledge base is declarative. The rules are written declaratively in an extension datalogs of the well-known deductive database language datalog on the data level, and additional datalogs rules can configure the processing of the annotated rules and the ontologies.
Cite as

Dietmar Seipel, Rüdiger von der Weth, Salvador Abreu, Falco Nogatz, and Alexander Werner. Declarative Rules for Annotated Expert Knowledge in Change Management. In 5th Symposium on Languages, Applications and Technologies (SLATE'16). Open Access Series in Informatics (OASIcs), Volume 51, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)

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@InProceedings{seipel_et_al:OASIcs.SLATE.2016.7,
  author =	{Seipel, Dietmar and von der Weth, R\"{u}diger and Abreu, Salvador and Nogatz, Falco and Werner, Alexander},
  title =	{{Declarative Rules for Annotated Expert Knowledge in Change Management}},
  booktitle =	{5th Symposium on Languages, Applications and Technologies (SLATE'16)},
  pages =	{7:1--7:16},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-95977-006-4},
  ISSN =	{2190-6807},
  year =	{2016},
  volume =	{51},
  editor =	{Mernik, Marjan and Leal, Jos\'{e} Paulo and Gon\c{c}alo Oliveira, Hugo},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.SLATE.2016.7},
  URN =		{urn:nbn:de:0030-drops-60124},
  doi =		{10.4230/OASIcs.SLATE.2016.7},
  annote =	{Keywords: declarative, datalog, prolog, domain-specific, change management}
}
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