97,757 research outputs found
Transformations of Logic Programs with Goals as Arguments
We consider a simple extension of logic programming where variables may range
over goals and goals may be arguments of predicates. In this language we can
write logic programs which use goals as data. We give practical evidence that,
by exploiting this capability when transforming programs, we can improve
program efficiency.
We propose a set of program transformation rules which extend the familiar
unfolding and folding rules and allow us to manipulate clauses with goals which
occur as arguments of predicates. In order to prove the correctness of these
transformation rules, we formally define the operational semantics of our
extended logic programming language. This semantics is a simple variant of
LD-resolution. When suitable conditions are satisfied this semantics agrees
with LD-resolution and, thus, the programs written in our extended language can
be run by ordinary Prolog systems.
Our transformation rules are shown to preserve the operational semantics and
termination.Comment: 51 pages. Full version of a paper that will appear in Theory and
Practice of Logic Programming, Cambridge University Press, U
Description and Optimization of Abstract Machines in a Dialect of Prolog
In order to achieve competitive performance, abstract machines for Prolog and
related languages end up being large and intricate, and incorporate
sophisticated optimizations, both at the design and at the implementation
levels. At the same time, efficiency considerations make it necessary to use
low-level languages in their implementation. This makes them laborious to code,
optimize, and, especially, maintain and extend. Writing the abstract machine
(and ancillary code) in a higher-level language can help tame this inherent
complexity. We show how the semantics of most basic components of an efficient
virtual machine for Prolog can be described using (a variant of) Prolog. These
descriptions are then compiled to C and assembled to build a complete bytecode
emulator. Thanks to the high level of the language used and its closeness to
Prolog, the abstract machine description can be manipulated using standard
Prolog compilation and optimization techniques with relative ease. We also show
how, by applying program transformations selectively, we obtain abstract
machine implementations whose performance can match and even exceed that of
state-of-the-art, highly-tuned, hand-crafted emulators.Comment: 56 pages, 46 figures, 5 tables, To appear in Theory and Practice of
Logic Programming (TPLP
Improving Prolog programs: Refactoring for Prolog
Refactoring is an established technique from the object-oriented (OO)
programming community to restructure code: it aims at improving software
readability, maintainability and extensibility. Although refactoring is not
tied to the OO-paradigm in particular, its ideas have not been applied to Logic
Programming until now.
This paper applies the ideas of refactoring to Prolog programs. A catalogue
is presented listing refactorings classified according to scope. Some of the
refactorings have been adapted from the OO-paradigm, while others have been
specifically designed for Prolog. The discrepancy between intended and
operational semantics in Prolog is also addressed by some of the refactorings.
In addition, ViPReSS, a semi-automatic refactoring browser, is discussed and
the experience with applying ViPReSS to a large Prolog legacy system is
reported. The main conclusion is that refactoring is both a viable technique in
Prolog and a rather desirable one.Comment: To appear in Theory and Practice of Logic Programming (TPLP
Generating Efficient, Terminating Logic Programs
The objective of control generation in logic programming is to automatically derive a computation rule for a program that is efficient and yet does not compromise program correctness. Progress in solving this important problem has been slow and, to date, only partial solutions have been proposed where the generated programs are either incorrect or inefficient. We show how the control generation problem can be tackled with a simple automatic transformation that relies on information about the depths of derivations. To prove correctness of our transform we introduce the notion of a semi delay recurrent program which generalises previous ideas in the termination literature for reasoning about logic programs with dynamic selection rules
The PITA System: Tabling and Answer Subsumption for Reasoning under Uncertainty
Many real world domains require the representation of a measure of
uncertainty. The most common such representation is probability, and the
combination of probability with logic programs has given rise to the field of
Probabilistic Logic Programming (PLP), leading to languages such as the
Independent Choice Logic, Logic Programs with Annotated Disjunctions (LPADs),
Problog, PRISM and others. These languages share a similar distribution
semantics, and methods have been devised to translate programs between these
languages. The complexity of computing the probability of queries to these
general PLP programs is very high due to the need to combine the probabilities
of explanations that may not be exclusive. As one alternative, the PRISM system
reduces the complexity of query answering by restricting the form of programs
it can evaluate. As an entirely different alternative, Possibilistic Logic
Programs adopt a simpler metric of uncertainty than probability. Each of these
approaches -- general PLP, restricted PLP, and Possibilistic Logic Programming
-- can be useful in different domains depending on the form of uncertainty to
be represented, on the form of programs needed to model problems, and on the
scale of the problems to be solved. In this paper, we show how the PITA system,
which originally supported the general PLP language of LPADs, can also
efficiently support restricted PLP and Possibilistic Logic Programs. PITA
relies on tabling with answer subsumption and consists of a transformation
along with an API for library functions that interface with answer subsumption
Defeasible Logic Programming: An Argumentative Approach
The work reported here introduces Defeasible Logic Programming (DeLP), a
formalism that combines results of Logic Programming and Defeasible
Argumentation. DeLP provides the possibility of representing information in the
form of weak rules in a declarative manner, and a defeasible argumentation
inference mechanism for warranting the entailed conclusions.
In DeLP an argumentation formalism will be used for deciding between
contradictory goals. Queries will be supported by arguments that could be
defeated by other arguments. A query q will succeed when there is an argument A
for q that is warranted, ie, the argument A that supports q is found undefeated
by a warrant procedure that implements a dialectical analysis.
The defeasible argumentation basis of DeLP allows to build applications that
deal with incomplete and contradictory information in dynamic domains. Thus,
the resulting approach is suitable for representing agent's knowledge and for
providing an argumentation based reasoning mechanism to agents.Comment: 43 pages, to appear in the journal "Theory and Practice of Logic
Programming
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