  The paper introduces fuzzy linguistic logic programming, which is a
combination of fuzzy logic programming, introduced by P. Vojtas, and hedge
algebras in order to facilitate the representation and reasoning on human
knowledge expressed in natural languages. In fuzzy linguistic logic
programming, truth values are linguistic ones, e.g., VeryTrue,
VeryProbablyTrue, and LittleFalse, taken from a hedge algebra of a linguistic
truth variable, and linguistic hedges (modifiers) can be used as unary
connectives in formulae. This is motivated by the fact that humans reason
mostly in terms of linguistic terms rather than in terms of numbers, and
linguistic hedges are often used in natural languages to express different
levels of emphasis. The paper presents: (i) the language of fuzzy linguistic
logic programming; (ii) a declarative semantics in terms of Herbrand
interpretations and models; (iii) a procedural semantics which directly
manipulates linguistic terms to compute a lower bound to the truth value of a
query, and proves its soundness; (iv) a fixpoint semantics of logic programs,
and based on it, proves the completeness of the procedural semantics; (v)
several applications of fuzzy linguistic logic programming; and (vi) an idea of
implementing a system to execute fuzzy linguistic logic programs.
