Similarity-Based Equality with Lazy Evaluation

Abstract

Thanks to the high expressive power and the rule-based nature of declarative languages, their influences are growing in the fields of AI, knowledge representation, and so on. On the other hand, since the notion of "equality" plays a crucial role on such languages, in this paper we focus in the design of a flexible (fuzzy) but efficient (lazy) notion of equality for hybrid declarative languages amalgamating functional-fuzzy-logic features. Here, we show that, by extending at a very low cost the notion of "strict equality" typically used in lazy functional-logic languages (Curry, Toy), and by relaxing it to the more flexible one of similar equality used in fuzzy-logic programming languages (Likelog, Bousi~Prolog), similarity relations can be successfully treated while mathematical functions are lazily evaluated in a given program. Our method represents a very easy, low-cost way, for fuzzifying lazy functional-logic languages and it can be implemented at a very high abstraction level by simply performing a static pre-process at compilation time which only manipulates the program at a syntactic level (i.e., the underlying operational mechanism based on rewriting/narrowing remains untouched). © Springer-Verlag Berlin Heidelberg 2010.