Conclusions

Abstract

With the ever-growing importance of computers in our modern-day society, the need for languages that allow to quickly write non-defective programs instructing these machines is pressing. While programming languages have come a long way since the days of punched cards, the large number of errors in current software shows that we have not yet attained this goal. A growing trend in computer science is to solve problems using a language-oriented approach. The idea is that instead of solving a problem in a general-purpose programming language such as Java or Haskell, we first create a domain-specific language that is very close to the problem domain and then model the problem in this high-level language. The advantage of this approach is that programs can be written much faster and that it becomes easier to spot differences between the implementation and the intentions of the programmer. One such domain-specific language is answer set programming (ASP). ASP is a declarative programming language with roots in logic programming that allows to model combinatorial optimization problems in a concise and elegant manner. Among others it has been used to implement planning problems, configuration optimizations and decision support systems. Furthermore it has also been used as an intermediate language for other domain-specific languages, such as those used for modeling biological networks. However, while ASP provides a rich language for modeling combinatorial problems, it is not directly suitable for modeling problems with continuous domains. Such problems occur naturally in diverse fields such as the design of gas and electricity networks, computer vision, business process management and investment portfolios. To overcome this problem, we studied the combination of ASP with fuzzy logic—a class of multi-valued logics that can handle continuity. The resulting formalism is called fuzzy answer set programming (FASP). After a short chapter that recalled some preliminary notions on ASP and fuzzy logic we described FASP in Chap. 3.