Abstract Logic programming is a flexible paradigm due to the use of predicates without fixed data flow. To extend logic languages with compact notation functional programming, there are various proposals map evaluable functions into in order stay framework. Since amalgamated offer as well efficient evaluation strategies, we propose an opposite approach this paper. By mapping programs transforma...

We present a method of embedding substructural logics into ordinary first-order intuitionistic logic. This embedding is faithful in a very strong sense: not only does it preserve provability of sequents under translation, but it also preserves sets of proofs — and the focusing structure of those proofs — up to isomorphism. Examples are given for the cases of intuitionistic linear logic and orde...

in this article, a speed control of dc motor is designed and illustrated using fuzzy logic-based programmable logic controller (plc). the dc motor is an attractive part of electrical equipment in many industrial applications requiring variable speed and load specifications due to its ease of controllability. the designed system is consisted of three main parts including programmable logic contr...

Despite the rapid emergence and success of Inductive Logic Programming, problems still surround number handling|problems directly inherited from the choice of logic programs as the representation language. Our conjecture is that a generalisation of the representation language to Constraint Logic Programs provides an eeective solution to this problem. We support this claim with the presentation ...

The predictive accuracy of a learning algorithm can be split into specificity and sensitivity, amongst other decompositions. Sensitivity, also known as completeness, is the ratio of true positives to the total number of positive examples, while specificity is the ratio of true negative to the total negative examples. In top-down learning methods of inductive logic programming, there is generall...

The learning system Progol5 and the underlying inference method of Bottom Generalisation are firmly established within Inductive Logic Programming (ILP). But despite their success, it is known that Bottom Generalisation, and therefore Progol5, are restricted to finding hypotheses that lie within the semantics of Plotkin’s relative subsumption. This paper exposes a previously unknown incompleten...

A Linear Logic automaton is a hybrid of a finite automaton and a non-deterministic Petri net. LL automata commands are represented by propositional Horn Linear Logic formulas. Computations performed by LL automata directly correspond to cut-free derivations in Linear Logic. A programming language of LL automata is developed in which typical sequential, nondeterministic and parallel programming ...