Fuzzy answer set programming: from theory to practice

Mushthofa, Mushthofa, Schockaert, Steven ORCID: https://orcid.org/0000-0002-9256-2881 and De Cock, Martine 2020. Fuzzy answer set programming: from theory to practice. Kosheleva, Olga, Shary, Sergey P., Xiang, Gang and Zapatrin, Roman, eds. Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications, Vol. 835. Studies in Computational Intelligence, Springer, 213–228. (10.1007/978-3-030-31041-7_12)

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Abstract

In this chapter, we give an introduction to Fuzzy Answer Set Programming (FASP), as well as a description of a state-of-the-art FASP solver and its use in practice. FASP is an extension of Answer Set Programming (ASP), a well known declarative language that allows users to specify combinatorial search and optimization problems in an intuitive way. By combining ASP with fuzzy logic, FASP is capable of expressing continuous optimization problems. In the chapter, we provide a high-level explanation of how ASP is typically used for solving problems, and the role that an extension to FASP can play in applications. We present the syntax and semantics of FASP, and describe how FASP programs are used to encode problems. We subsequently explain how our solver finds the answer sets of a FASP program, and we illustrate the whole workflow using an application for modeling of gene regulatory networks.

Item Type:	Book Section
Date Type:	Publication
Status:	Published
Schools:	Computer Science & Informatics
Publisher:	Springer
ISBN:	9783030310400
Date of First Compliant Deposit:	18 January 2018
Last Modified:	26 Apr 2024 10:15
URI:	https://orca.cardiff.ac.uk/id/eprint/107555

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