Order-sorted feature (OSF) logic is a knowledge representation and reasoning language based on sorts-symbols that denote concepts ordered in a subsumption relation-and features-symbols that denote functional attribute...
详细信息
Order-sorted feature (OSF) logic is a knowledge representation and reasoning language based on sorts-symbols that denote concepts ordered in a subsumption relation-and features-symbols that denote functional attributes. Reasoning with OSF logic is based on the unification of OSF terms, record-like structures that denote classes of objects and that are themselves ordered in a subsumption relation. OSF term unification aims to combine the constraints expressed by two terms in a consistent way, and it takes into account the subsumption relation between sort symbols, providing an efficient calculus of type subsumption. This article presents an approach to define approximate reasoning with OSF logic by extending its language with a similarity relation on sorts. In order for the OSF term unification algorithm to take into account this similarity and its interaction with the subsumption relation, we propose to combine the two relations into a single fuzzy subsumption relation. The advantage is that the same unification rules of OSF logic can then be applied to this fuzzy setting. We conclude by discussing potential applications of OSF logic extended with a sort similarity relation.
This article presents MP-SPILDL, a massively parallel inductive logic learner in Description logic (DL). MP-SPILDL is a scalable inductive logic programming (ILP) algorithm that exploits existing Big Data infrastructu...
详细信息
This article presents MP-SPILDL, a massively parallel inductive logic learner in Description logic (DL). MP-SPILDL is a scalable inductive logic programming (ILP) algorithm that exploits existing Big Data infrastructure to perform large-scale inductive logic learning in DL (the ALCQI((D)) DL language in particular). MP-SPILDL targets accelerating both hypothesis search and hypothesis evaluation by aggregating the computing power of multi-core CPUs with their vector/SIMD instructions and multi-GPUs in a Hadoop cluster. In terms of hypothesis search, MP-SPILDL employs a novel MapReduce-based algorithm that performs distributed parallel hypothesis search. MP-SPILDL also employs a novel MapReduce-based procedure that eliminates all redundant hypotheses generated after each learning iteration. Moreover, MP-SPILDL utilizes deterministic ordering of hypotheses' operands to avoid exploring redundant areas of the search space, similar to the DL-Learner, the state of the art in DL-based ILP literature. In terms of hypothesis evaluation, MP-SPILDL performs parallel hypothesis evaluation, which uses all CPU cores combined with their vector instructions and all multi-GPUs of all machines in the Hadoop cluster. According to the experimental results using an Apache Spark implementation on a Hadoop cluster of three worker machines (36 total CPU cores, 7 total GPUs), MP-SPILDL achieved speedups of up to 13.3 folds using parallel beam search with $beamWidth = 32 and CPU-based vectorized hypothesis evaluation - the best-case scenario. On small datasets such as Michalski's trains, MP-SPILDL achieved a slower performance than the baseline, representing the worst-case scenario.
We explore how Large Language Models (LLMs) can function not just as databases, but as dynamic, end-user programmable neural computers. The native programming language for this neural computer is a logic programming-i...
详细信息
This note presents a historical survey of informal semantics that are associated with logic programming under answer set semantics. We review these in uniform terms and align them with two paradigms: Answer Set Progra...
详细信息
This note presents a historical survey of informal semantics that are associated with logic programming under answer set semantics. We review these in uniform terms and align them with two paradigms: Answer Set programming and ASP-Prolog - two prominent Knowledge Representation and Reasoning Paradigms in Artificial Intelligence.
WordNet is a lexical database for English that is supplied in a variety of formats, including one compatible with the Prolog programming language. Given the success and usefulness of WordNet, wordnets of other languag...
详细信息
WordNet is a lexical database for English that is supplied in a variety of formats, including one compatible with the Prolog programming language. Given the success and usefulness of WordNet, wordnets of other languages have been developed, including Spanish. The Spanish WordNet, like others, does not provide a version compatible with Prolog. This work aims to fill this gap by translating the Multilingual Central Repository (MCR) version of the Spanish WordNet into a Prolog-compatible format. Thanks to this translation, a set of Spanish lexical databases are obtained, which allows access to WordNet information using declarative techniques and the deductive capabilities of the Prolog language. Also, this work facilitates the development of other programs to analyze the obtained information. Remarkably, we have adapted the technique of differential testing, used in software testing, to verify the correctness of this conversion. In addition, to ensure the consistency of the generated Prolog databases, as well as the databases from which we started, a complete series of integrity constraint tests have been carried out. In this way we have discovered some inconsistency problems in the MCR databases that have a reflection in the generated Prolog databases and have been reported to the owners of those databases.
Indexing is generally viewed as an implementation artifact, indispensable to speed up the execution of logic programs and theorem provers, but with little intrinsically logical about it. We show that indexing can be g...
详细信息
KW-GPS is a system to assist users intent on enjoying Web resources related to a domain-restricted collection of stories. In this system, each story is referenced in a virtual library in terms of the following data: (...
详细信息
Datalog has gained prominence in program analysis due to its expressiveness and ease of use. Its generic fixpoint resolution algorithm over relational domains simplifies the expression of many complex analyses. The pe...
详细信息
Datalog has gained prominence in program analysis due to its expressiveness and ease of use. Its generic fixpoint resolution algorithm over relational domains simplifies the expression of many complex analyses. The performance and scalability issues of early Datalog approaches have been addressed by tools such as Souffle through specialized code generation. Still, while pure Datalog is expressive enough to support a wide range of analyses, there is a growing need for extensions to accommodate increasingly complex analyses. This has led to the development of various extensions, such as Flix, Datafun, and Formulog, which enhance Datalog with features like arbitrary lattices and SMT constraints. Most of these extensions recognize the need for full interoperability between Datalog and a full-fledged programming language, a functionality that high-performance systems like Souffle lack. Speciflcally, in most cases, they construct languages from scratch with first-class Datalog support, allowing greater flexibility. However, this flexibility often comes at the cost of performance due to the conflicting requirements of prioritizing modularity and abstraction over efficiency. Consequently, achieving both flexibility and compilation to highly-performant specialized code poses a significant challenge. In this work, we reconcile the competing demands of expressiveness and performance with Flan, a Datalog compiler fully embedded in Scala that leverages multi-stage programming to generate specialized code for enhanced performance. Our approach combines the flexibility of Flix with Souffle's performance, offering seamless integration with the host language that enables the addition of powerful extensions while generating specialized code for the entire computation. Flan's simple operator interface allows the addition of an extensive set of features, including arbitrary aggregates, user-defined functions, and lattices, with multiple execution strategies such as binary and multi-way
A logic programming approach to the intelligent monitoring of anomalous human activity is considered. The main idea of this approach is in using of a first order logic for describing abstract concepts of anomalous hum...
详细信息
We analyze the declarative encoding of the set-theoretic graph property known as bisimulation. This notion is of central importance in non-well founded set theory, semantics of concurrency, model checking, and coinduc...
详细信息
We analyze the declarative encoding of the set-theoretic graph property known as bisimulation. This notion is of central importance in non-well founded set theory, semantics of concurrency, model checking, and coinductive reasoning. From a modeling point of view, it is particularly interesting since it allows two alternative high-level characterizations. We analyze the encoding style of these modelings in various dialects of logic programming. Moreover, the notion also admits a polynomialtime maximum fix point procedure that we implemented in Prolog. Similar graph problems which are NP hard or not yet perfectly classified (e.g., graph isomorphism) can benefit from the encodings presented.
暂无评论