612 research outputs found
Abstract Canonical Inference
An abstract framework of canonical inference is used to explore how different
proof orderings induce different variants of saturation and completeness.
Notions like completion, paramodulation, saturation, redundancy elimination,
and rewrite-system reduction are connected to proof orderings. Fairness of
deductive mechanisms is defined in terms of proof orderings, distinguishing
between (ordinary) "fairness," which yields completeness, and "uniform
fairness," which yields saturation.Comment: 28 pages, no figures, to appear in ACM Trans. on Computational Logi
Acceptability with general orderings
We present a new approach to termination analysis of logic programs. The
essence of the approach is that we make use of general orderings (instead of
level mappings), like it is done in transformational approaches to logic
program termination analysis, but we apply these orderings directly to the
logic program and not to the term-rewrite system obtained through some
transformation. We define some variants of acceptability, based on general
orderings, and show how they are equivalent to LD-termination. We develop a
demand driven, constraint-based approach to verify these
acceptability-variants.
The advantage of the approach over standard acceptability is that in some
cases, where complex level mappings are needed, fairly simple orderings may be
easily generated. The advantage over transformational approaches is that it
avoids the transformation step all together.
{\bf Keywords:} termination analysis, acceptability, orderings.Comment: To appear in "Computational Logic: From Logic Programming into the
Future
Web ontology representation and reasoning via fragments of set theory
In this paper we use results from Computable Set Theory as a means to
represent and reason about description logics and rule languages for the
semantic web.
Specifically, we introduce the description logic \mathcal{DL}\langle
4LQS^R\rangle(\D)--admitting features such as min/max cardinality constructs
on the left-hand/right-hand side of inclusion axioms, role chain axioms, and
datatypes--which turns out to be quite expressive if compared with
\mathcal{SROIQ}(\D), the description logic underpinning the Web Ontology
Language OWL. Then we show that the consistency problem for
\mathcal{DL}\langle 4LQS^R\rangle(\D)-knowledge bases is decidable by
reducing it, through a suitable translation process, to the satisfiability
problem of the stratified fragment of set theory, involving variables
of four sorts and a restricted form of quantification. We prove also that,
under suitable not very restrictive constraints, the consistency problem for
\mathcal{DL}\langle 4LQS^R\rangle(\D)-knowledge bases is
\textbf{NP}-complete. Finally, we provide a -translation of rules
belonging to the Semantic Web Rule Language (SWRL)
Implementation considerations in supervisory control
With supervisory control theory it is possible to describe controllers which influence the behaviour of a system by disabling controllable events. But sometimes it is desirable to have a controller which not only disables controllable events but also chooses one among the enabled ones. This event can be interpreted as a command given to the plant. This idea is formalized in the concept of an implementation, which is a special supervisor, enabling at most one controllable event at a time. In this paper, some useful properties are introduced, which ensure, when met, that each implementation of a given DES is nonblocking. The approach is applied to a simple chemical batch process example
Analysis of Probabilistic Basic Parallel Processes
Basic Parallel Processes (BPPs) are a well-known subclass of Petri Nets. They
are the simplest common model of concurrent programs that allows unbounded
spawning of processes. In the probabilistic version of BPPs, every process
generates other processes according to a probability distribution. We study the
decidability and complexity of fundamental qualitative problems over
probabilistic BPPs -- in particular reachability with probability 1 of
different classes of target sets (e.g. upward-closed sets). Our results concern
both the Markov-chain model, where processes are scheduled randomly, and the
MDP model, where processes are picked by a scheduler.Comment: This is the technical report for a FoSSaCS'14 pape
The dependency pair framework: Combining techniques for automated termination proofs
Abstract. The dependency pair approach is one of the most powerful techniques for automated termination proofs of term rewrite systems. Up to now, it was regarded as one of several possible methods to prove termination. In this paper, we show that dependency pairs can instead be used as a general concept to integrate arbitrary techniques for termination analysis. In this way, the benefits of different techniques can be combined and their modularity and power are increased significantly. We refer to this new concept as the “dependency pair framework ” to distinguish it from the old “dependency pair approach”. Moreover, this framework facilitates the development of new methods for termination analysis. To demonstrate this, we present several new techniques within the dependency pair framework which simplify termination problems considerably. We implemented the dependency pair framework in our termination prover AProVE and evaluated it on large collections of examples.
Proof Relevant Corecursive Resolution
Resolution lies at the foundation of both logic programming and type class
context reduction in functional languages. Terminating derivations by
resolution have well-defined inductive meaning, whereas some non-terminating
derivations can be understood coinductively. Cycle detection is a popular
method to capture a small subset of such derivations. We show that in fact
cycle detection is a restricted form of coinductive proof, in which the atomic
formula forming the cycle plays the role of coinductive hypothesis.
This paper introduces a heuristic method for obtaining richer coinductive
hypotheses in the form of Horn formulas. Our approach subsumes cycle detection
and gives coinductive meaning to a larger class of derivations. For this
purpose we extend resolution with Horn formula resolvents and corecursive
evidence generation. We illustrate our method on non-terminating type class
resolution problems.Comment: 23 pages, with appendices in FLOPS 201
First-order formative rules
This paper discusses the method of formative rules for first-order term rewriting, which was previously defined for a higher-order setting. Dual to the well-known usable rules, formative rules allow dropping some of the term constraints that need to be solved during a termination proof. Compared to the higher-order definition, the first-order setting allows for significant improvements of the technique
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