We present a new fuzzy logic programming Language, called LIKELOG, to be used for approximated reat;oning and for fuzzy deductive database applications. The core component of the system is the algori thm of unification, which expands the Martelli-Montanari unification algorithm introducing two similarity relations. The resolution mechanism is a straightforward application of this kind of expand...

1 Project Supported by the National Hi Tech Research & Development Program (863) of China (No. 2002AA413420) ABSTRACT This paper imports the fuzzy logic into image retrieval to deal with the vagueness and ambiguity of human judgment of image similarity. Our retrieval system has the following properties: firstly adopting the fuzzy language variables to describe the similarity degree of image fea...

Since the basic probability of an interval-valued belief structure (IBS) is assigned as interval number, its combination becomes difficult. Especially, when dealing with highly conflicting IBSs, most existing methods may cause counter-intuitive results, which can bring extra heavy computational burden due to nonlinear optimization model, and lose good property associativity commutativity in Dem...

We introduce a weighted logic with discounting and we establish Büchi’s and Elgot’s theorem for weighted automata over finite words and arbitrary commutative semirings. Then we investigate Büchi and Muller automata with discounting over the max-plus and the min-plus semiring. We show their expressive equivalence with weighted MSO-sentences with discounting. In this case our logic has a purely s...

The objective of this paper is to establish a class of models for solving the weight problem in fuzzy logic. First, some constraints that weighted fuzzy logic should satisfy are given based on Triangular norms and conorms. Then, based on these constraints, a class of models (referred to as relative weighted models) are established for handling weights in fuzzy logic. These models are novel in t...

We introduce a weighted linear dynamic logic (weighted LDL for short) and show the expressive equivalence of its formulas to weighted rational expressions. This adds a new characterization for recognizable series to the fundamental Schützenberger theorem. Surprisingly, the equivalence does not require any restriction to our weighted LDL. Our results hold over arbitrary (resp. totally complete) ...

Markov logic is a robust approach for probabilistic relational knowledge representation that uses a log-linear model of weighted first-order formulas for probabilistic reasoning. This loglinear model always exists but may not represent the knowledge engineer’s intentions adequately. In this paper, we develop a general framework for measuring this coherence of Markov logic networks by comparing ...

Weighted logic programming, a generalization of bottom-up logic programming, is a successful framework for specifying dynamic programming algorithms. In this setting, proofs correspond to the algorithm’s output space, such as a path through a graph or a grammatical derivation, and are given a weighted score, often interpreted as a probability, that depends on the score of the base axioms used i...