239 research outputs found
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
Logic-Based Decision Support for Strategic Environmental Assessment
Strategic Environmental Assessment is a procedure aimed at introducing
systematic assessment of the environmental effects of plans and programs. This
procedure is based on the so-called coaxial matrices that define dependencies
between plan activities (infrastructures, plants, resource extractions,
buildings, etc.) and positive and negative environmental impacts, and
dependencies between these impacts and environmental receptors. Up to now, this
procedure is manually implemented by environmental experts for checking the
environmental effects of a given plan or program, but it is never applied
during the plan/program construction. A decision support system, based on a
clear logic semantics, would be an invaluable tool not only in assessing a
single, already defined plan, but also during the planning process in order to
produce an optimized, environmentally assessed plan and to study possible
alternative scenarios. We propose two logic-based approaches to the problem,
one based on Constraint Logic Programming and one on Probabilistic Logic
Programming that could be, in the future, conveniently merged to exploit the
advantages of both. We test the proposed approaches on a real energy plan and
we discuss their limitations and advantages.Comment: 17 pages, 1 figure, 26th Int'l. Conference on Logic Programming
(ICLP'10
On the Implementation of the Probabilistic Logic Programming Language ProbLog
The past few years have seen a surge of interest in the field of
probabilistic logic learning and statistical relational learning. In this
endeavor, many probabilistic logics have been developed. ProbLog is a recent
probabilistic extension of Prolog motivated by the mining of large biological
networks. In ProbLog, facts can be labeled with probabilities. These facts are
treated as mutually independent random variables that indicate whether these
facts belong to a randomly sampled program. Different kinds of queries can be
posed to ProbLog programs. We introduce algorithms that allow the efficient
execution of these queries, discuss their implementation on top of the
YAP-Prolog system, and evaluate their performance in the context of large
networks of biological entities.Comment: 28 pages; To appear in Theory and Practice of Logic Programming
(TPLP
Logic Programming and Logarithmic Space
We present an algebraic view on logic programming, related to proof theory
and more specifically linear logic and geometry of interaction. Within this
construction, a characterization of logspace (deterministic and
non-deterministic) computation is given via a synctactic restriction, using an
encoding of words that derives from proof theory.
We show that the acceptance of a word by an observation (the counterpart of a
program in the encoding) can be decided within logarithmic space, by reducing
this problem to the acyclicity of a graph. We show moreover that observations
are as expressive as two-ways multi-heads finite automata, a kind of pointer
machines that is a standard model of logarithmic space computation
Towards Correctness of Program Transformations Through Unification and Critical Pair Computation
Correctness of program transformations in extended lambda calculi with a
contextual semantics is usually based on reasoning about the operational
semantics which is a rewrite semantics. A successful approach to proving
correctness is the combination of a context lemma with the computation of
overlaps between program transformations and the reduction rules, and then of
so-called complete sets of diagrams. The method is similar to the computation
of critical pairs for the completion of term rewriting systems. We explore
cases where the computation of these overlaps can be done in a first order way
by variants of critical pair computation that use unification algorithms. As a
case study we apply the method to a lambda calculus with recursive
let-expressions and describe an effective unification algorithm to determine
all overlaps of a set of transformations with all reduction rules. The
unification algorithm employs many-sorted terms, the equational theory of
left-commutativity modelling multi-sets, context variables of different kinds
and a mechanism for compactly representing binding chains in recursive
let-expressions.Comment: In Proceedings UNIF 2010, arXiv:1012.455
Ranking Services Using Fuzzy HEX Programs
Abstract. The need to reason with knowledge expressed in both Logic Program-ming (LP) and Description Logics (DLs) paradigms on the Semantic Web lead to several integrating formalisms, e.g., Description Logic programs (dl-programs) allow a logic program to retrieve results from and feed results to a DL knowledge base. Two functional extensions of dl-programs are HEX programs and fuzzy dl-programs. The former abstract away from DLs, allowing for general exter-nal queries, the latter deal with the uncertain, vague, and inconsistent nature of knowledge on the Web by means of fuzzy logic mechanisms. In this paper, we generalize both HEX programs and fuzzy dl-programs to fuzzy HEX programs: a LP-based paradigm, supporting both fuzziness as well as reasoning with exter-nal sources. We define basic syntax and semantics and analyze the framework semantically, e.g., by investigating the complexity. Additionally, we provide a translation from fuzzy HEX programs to HEX programs, enabling an implementa-tion via the dlvhex reasoner. Finally, we illustrate the use of fuzzy HEX programs for ranking services by using them to model non-functional properties of services and user preferences.
Modular Nonmonotonic Logic Programming Revisited
Abstract. Recently, enabling modularity aspects in Answer Set Programming (ASP) has gained increasing interest to ease the composition of program parts to an overall program. In this paper, we focus on modular nonmonotonic logic programs (MLP) under the answer set semantics, whose modules may have contextually de-pendent input provided by other modules. Moreover, (mutually) recursive module calls are allowed. We define a model-theoretic semantics for this extended setting, show that many desired properties of ordinary logic programming generalize to our modular ASP, and determine the computational complexity of the new formalism. We investigate the relationship of modular programs to disjunctive logic programs with well-defined input/output interface (DLP-functions) and show that they can be embedded into MLPs
- âŠ