650 research outputs found
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
Datalog with Negation and Monotonicity
Positive Datalog has several nice properties that are lost when the language is extended with negation. One example is that fixpoints of positive Datalog programs are robust w.r.t. the order in which facts are inserted, which facilitates efficient evaluation of such programs in distributed environments. A natural question to ask, given a (stratified) Datalog program with negation, is whether an equivalent positive Datalog program exists.
In this context, it is known that positive Datalog can express only a strict subset of the monotone queries, yet the exact relationship between the positive and monotone fragments of semi-positive and stratified Datalog was previously left open. In this paper, we complete the picture by showing that monotone queries expressible in semi-positive Datalog exist which are not expressible in positive Datalog. To provide additional insight into this gap, we also characterize a large class of semi-positive Datalog programs for which the dichotomy `monotone if and only if rewritable to positive Datalog\u27 holds. Finally, we give best-effort techniques to reduce the amount of negation that is exhibited by a program, even if the program is not monotone
A decidable subclass of finitary programs
Answer set programming - the most popular problem solving paradigm based on
logic programs - has been recently extended to support uninterpreted function
symbols. All of these approaches have some limitation. In this paper we propose
a class of programs called FP2 that enjoys a different trade-off between
expressiveness and complexity. FP2 programs enjoy the following unique
combination of properties: (i) the ability of expressing predicates with
infinite extensions; (ii) full support for predicates with arbitrary arity;
(iii) decidability of FP2 membership checking; (iv) decidability of skeptical
and credulous stable model reasoning for call-safe queries. Odd cycles are
supported by composing FP2 programs with argument restricted programs
ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answering
Question answering on knowledge bases (KBQA) poses a unique challenge for
semantic parsing research due to two intertwined factors: large search space
and ambiguities in schema linking. The predominant ranking-based KBQA models,
which rely on a candidate enumeration step to reduce the search space, struggle
with flexibility and have impractical online running time. In this paper, we
present ArcaneQA, a novel generation-based model that addresses both the large
search space and schema linking in a unified framework with two mutually
boosting ingredients: we use dynamic program induction to tackle the large
search space and dynamic contextualized encoding to enhance schema linking.
Experiment results on multiple popular KBQA datasets demonstrate the highly
competitive performance of ArcaneQA in both effectiveness and efficiency
Boolean dimension and tree-width
The dimension is a key measure of complexity of partially ordered sets. Small
dimension allows succinct encoding. Indeed if has dimension , then to
know whether in it is enough to check whether in each
of the linear extensions of a witnessing realizer. Focusing on the encoding
aspect Ne\v{s}et\v{r}il and Pudl\'{a}k defined a more expressive version of
dimension. A poset has boolean dimension at most if it is possible to
decide whether in by looking at the relative position of and
in only permutations of the elements of . We prove that posets with
cover graphs of bounded tree-width have bounded boolean dimension. This stays
in contrast with the fact that there are posets with cover graphs of tree-width
three and arbitrarily large dimension. This result might be a step towards a
resolution of the long-standing open problem: Do planar posets have bounded
boolean dimension?Comment: one more reference added; paper revised along the suggestion of three
reviewer
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