Encoding higher level extensions of Petri nets in answer set programming

Saadat Anwar, Chitta Baral, Katsumi Inoue

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

Answering realistic questions about biological systems and pathways similar to text book questions used for testing students' understanding of such systems is one of our long term research goals. Often these questions require simulation based reasoning. In this paper, we show how higher level extensions of Petri Nets, such as colored tokens can be encoded in Answer Set Programming, thereby providing the right formalisms to model and reason about such questions with relative ease. Our approach can be adapted to other domains.

Original languageEnglish (US)
Title of host publicationLogic Programming and Nonmonotonic Reasoning - 12th International Conference, LPNMR 2013, Proceedings
Pages116-121
Number of pages6
DOIs
StatePublished - Oct 22 2013
Event12th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2013 - Corunna, Spain
Duration: Sep 15 2013Sep 19 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8148 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Logic Programming and Nonmonotonic Reasoning, LPNMR 2013
CountrySpain
CityCorunna
Period9/15/139/19/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Encoding higher level extensions of Petri nets in answer set programming'. Together they form a unique fingerprint.

  • Cite this

    Anwar, S., Baral, C., & Inoue, K. (2013). Encoding higher level extensions of Petri nets in answer set programming. In Logic Programming and Nonmonotonic Reasoning - 12th International Conference, LPNMR 2013, Proceedings (pp. 116-121). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8148 LNAI). https://doi.org/10.1007/978-3-642-40564-8_12