Cooperating Answer Set Programming

Aims and scope of the seriesThe series 'Atlantis Computational Intelligence Systems' aims at covering state-of-theart research and development in all fields where computational intelligence is investigated and applied. The series seeks to publish monographs and edited volumes on foundations and new developments in the field of computational intelligence, including fundamental and applied research as well as work describing new, emerging technologies originating from computational intelligence research. Applied CI research may range from CI applications in the industry to research projects in the life sciences, including research in biology, physics, chemistry and the neurosciences.All books in this series are co-published with Springer.For more information on this series and our other book series, please visit our website at:www.atlantis-press.comPreface Answer set programming (ASP) is a form of logic programming that originated at the end of the 1980s and the beginning of the 1990s. It is especially tailored towards solving hard search problems, which it allows to encode concisely. In the past two decades it has known great success and has -among others -been applied to planning problems, musical composition, biological modeling and decision support systems for the space shuttle. Unfortunately, ASP is not very well equipped for modeling problems in continuous domains. In this book we attempt to augment ASP with the capability of expressing continuous problems by creating an answer set programming framework based on fuzzy logic. The resulting language is called fuzzy answer set programming (FASP). After two introductory chapters, also introducing the necessary technical background, we study FASP and its extensions in Chapters 3 and 4. Then we focus on the question of whether the many extensions of FASP can be compiled to a core language in Chapter 5 and succeedingly study an implementation method for a subset of FASP in Chapter 6. As such, we focus both on theoretical aspects of the language as on more practical aspects such as implementation.

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“…The terminology is based on material from [Van Nieuwenborgh (2005)]. The terminology is based on material from [Van Nieuwenborgh (2005)].…”

Section: Definitionsmentioning

confidence: 99%

Answer Set Programming for Continuous Domains: A Fuzzy Logic Approach

Janssen¹,

Schockaert²,

Vermeir³

et al. 2012

Atlantis Computational Intelligence Systems

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“…For simple programs, the minimal fuzzy model exists and is unique [24]. Similar to ASP, minimal fuzzy models of simple FASP programs can be characterized by forward chaining, as illustrated below and subsequently defined more formally.…”

Section: Simple Programs and Answer Setsmentioning

confidence: 99%

Fuzzy Answer Set Programming

Nieuwenborgh

Cock

Vermeir

2006

Logics in Artificial Intelligence

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In this chapter, we present a tutorial about fuzzy answer set programming (FASP); we give a gentle introduction to its basic ideas and definitions. FASP is a combination of answer set programming and fuzzy logics which has recently been proposed. From the answer set semantics, FASP inherits the declarative nonmonotonic reasoning capabilities, while fuzzy logic adds the power to model continuous problems. FASP can be tailored towards different applications since fuzzy logics gives a great flexibility, e.g. by the possibility to use different generalizations of the classical connectives. In this chapter, we consider a rather general form of FASP programs; the connectives can in principal be interpreted by arbitrary [0, 1] n → [0, 1]-mappings. Despite that very general connectives are allowed, the presented framework turns out to be an intuitive extension of answer set programming.

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