688 research outputs found
(Co-)Inductive semantics for Constraint Handling Rules
In this paper, we address the problem of defining a fixpoint semantics for
Constraint Handling Rules (CHR) that captures the behavior of both
simplification and propagation rules in a sound and complete way with respect
to their declarative semantics. Firstly, we show that the logical reading of
states with respect to a set of simplification rules can be characterized by a
least fixpoint over the transition system generated by the abstract operational
semantics of CHR. Similarly, we demonstrate that the logical reading of states
with respect to a set of propagation rules can be characterized by a greatest
fixpoint. Then, in order to take advantage of both types of rules without
losing fixpoint characterization, we present an operational semantics with
persistent. We finally establish that this semantics can be characterized by
two nested fixpoints, and we show the resulting language is an elegant
framework to program using coinductive reasoning.Comment: 17 page
Productive Corecursion in Logic Programming
Logic Programming is a Turing complete language. As a consequence, designing
algorithms that decide termination and non-termination of programs or decide
inductive/coinductive soundness of formulae is a challenging task. For example,
the existing state-of-the-art algorithms can only semi-decide coinductive
soundness of queries in logic programming for regular formulae. Another, less
famous, but equally fundamental and important undecidable property is
productivity. If a derivation is infinite and coinductively sound, we may ask
whether the computed answer it determines actually computes an infinite
formula. If it does, the infinite computation is productive. This intuition was
first expressed under the name of computations at infinity in the 80s. In
modern days of the Internet and stream processing, its importance lies in
connection to infinite data structure processing.
Recently, an algorithm was presented that semi-decides a weaker property --
of productivity of logic programs. A logic program is productive if it can give
rise to productive derivations. In this paper we strengthen these recent
results. We propose a method that semi-decides productivity of individual
derivations for regular formulae. Thus we at last give an algorithmic
counterpart to the notion of productivity of derivations in logic programming.
This is the first algorithmic solution to the problem since it was raised more
than 30 years ago. We also present an implementation of this algorithm.Comment: Paper presented at the 33nd International Conference on Logic
Programming (ICLP 2017), Melbourne, Australia, August 28 to September 1, 2017
16 pages, LaTeX, no figure
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