共查询到20条相似文献,搜索用时 15 毫秒
1.
Julio Mariño Juan José Moreno-Navarro Susana Munoz-Hernandez 《New Generation Computing》2008,27(1):25-56
Although negation is an active area of research in logic programming, sound and complete implementations are still absent
from actual Prolog systems. One of the most promising techniques in the literature is intensional negation
(IN), which follows a transformational approach: for each predicate p in a program its negative counterpart intneg(p) is generated. However, implementations of IN have not been included in Prolog environments due, in part, to the lack of
details and explicit techniques, such as the treatment of universally quantified goals. In this paper, we describe a variant
of IN, which we have called constructive intensional negation
(CIN). Unlike earlier proposals, CIN does not resort to a dedicated resolution strategy when dealing with universally quantified
formulae, which has been instrumental in having an effective implementation. Therefore, pure SLD resolution is used, what
enables the reuse of existing Prolog implementation technology. Among the contributions of this work we can mention not only
a full implementation being tested for its integration in the Ciao Prolog system but also some formal results ensuring soundness
and completeness with their associated proofs.
相似文献
Susana Munoz-HernandezEmail: |
2.
Manolis Gergatsoulis Panos Rondogiannis Themis Panayiotopoulos 《New Generation Computing》2001,19(1):87-100
In this paper we introduce the logic programming languageDisjunctive Chronolog which combines the programming paradigms of temporal and disjunctive logic programming. Disjunctive Chronolog is capable
of expressing dynamic behaviour as well as uncertainty, two notions that are very common in a variety of real systems. We
present the minimal temporal model semantics and the fixpoint semantics for the new programming language and demonstrate their
equivalence. We also show how proof procedures developed for disjunctive logic programs can be easily extended to apply to
Disjunctive Chronolog programs.
Manolis Gergatsoulis, Ph.D.: He received his B.Sc. in Physics in 1983, the M.Sc. and the Ph.D. degrees in Computer Science in 1986 and 1995 respectively
all from the University of Athens, Greece. Since 1996 he is a Research Associate in the Institute of Informatics and Telecommunications,
NCSR ‘Demokritos’, Athens. His research interests include logic and temporal programming, program transformations and synthesis,
as well as theory of programming languages.
Panagiotis Rondogiannis, Ph.D.: He received his B.Sc. from the Department of Computer Engineering and Informatics, University of Patras, Greece, in 1989,
and his M.Sc. and Ph.D. from the Department of Computer Science, University of Victoria, Canada, in 1991 and 1994 respectively.
From 1995 to 1996 he served in the Greek army. From 1996 to 1997 he was a visiting professor in the Department of Computer
Science, University of Ioannina, Greece, and since 1997 he is a Lecturer in the same Department. In January 2000 he was elected
Assistant Professor in the Department of Informatics at the University of Athens. His research interests include functional,
logic and temporal programming, as well as theory of programming languages.
Themis Panayiotopoulos, Ph.D.: He received his Diploma on Electrical Engineering from the Department of Electrical Engineering, National Technical Univesity
of Athens, in 1984, and his Ph.D. on Artificial Intelligence from the above mentioned department in 1989. From 1991 to 1994
he was a visiting professor at the Department of Mathematics, University of the Aegean, Samos, Greece and a Research Associate
at the Institute of Informatics and Telecommunications of “Democritos” National Research Center. Since 1995 he is an Assistant
Prof. at the Department of Computer Science, University of Piraeus. His research interests include temporal programming, logic
programming, expert systems and intelligent agent architectures. 相似文献
3.
Peter A. Tinker 《International journal of parallel programming》1988,17(1):59-92
The research focus in parallel logic programming is shifting rapidly from theoretical considerations and simulation on uniprocessors to implementation on true multiprocessors. This report presents performance figures from such a system,Boplog, for OR-parallel Horn clause logic programs on the BBN Butterfly Parallel Processor. Boplog is designed expressly for a large scale shared memory multiprocessor with an Omega interconnect. The target machine and underlying execution model are described briefly. The primary focus of the paper is on detailed statistics taken from the execution of benchmark programs to assess the performance of the model and clarify the impact of design and architecture decisions. They show that while speedup of this implementation on highly OR-parallel problems is very good, overall performance is poor. Despite its speed drawback, many aspcts of the implementation and its performance can prove useful in designing future systems for similar machines. A binding model that prohibits constant time access to bindings, and the inability of the machine to support an ambitious use of machine memory appear to be most damaging factors.This work was carried out at the University of Utah, Salt Lake City, Utah. It was supported by a University of Utah Graduate Research Fellowship, the National Science Foundation under Grant DCR-856000, and by an unrestricted gift from L. M. Ericsson Telefon AB, Stockholm, Sweden, Production of the document was supported by the Rockwell International Science Center. 相似文献
4.
This paper present an extension of traditional logic programming, called ordered logic (OL) programming, to support classical
negation as well as constructs from the object-oriented paradigm. In particular, such an extension allows to cope with the
notions of object, multiple inheritance and non-monotonic reasoning.
The contribution of the work is mainly twofold. First, a rich wellfounded semantics for ordered logic programs is defined.
Second, an efficient method for the well-founded model computation of a meaningful class of ordered logic programs, called
stratified programs, is provided. 相似文献
5.
The bounded ILP-consistency problem for function-free Horn clauses is described as follows. Given at setE + andE ? of function-free ground Horn clauses and an integerk polynomial inE +∪E ?, does there exist a function-free Horn clauseC with no more thank literals such thatC subsumes each element inE + andC does not subsume any element inE ?? It is shown that this problem is Σ 2 P complete. We derive some related results on the complexity of ILP and discuss the usefulness of such complexity results. 相似文献
6.
Since feature models for realistic product families may be quite complicated, the automated analysis of feature models is desirable. Although several approaches reported in the literature address this issue, complex cross-tree relationships involving attributes in extended feature models have not been handled. In this article, we introduce a mapping from extended feature models to constraint logic programming over finite domains. This mapping is used to translate into constraint logic programs; basic, cardinality-based and extended feature models, which can include complex cross-tree relationships involving attributes. This translation enables the use of off-the-shelf constraint solvers for the automated analysis of extended feature models involving such complex relationships. We also present the performance results of some well-known analysis operations on an example translated model. 相似文献
7.
M. I. Sessa 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》2001,5(2):160-170
In order to provide approximate reasoning capabilities, in Gerla G, Sessa MI (1999) Chen G, Ying M, Cai K-Y (Eds) Fuzzy Logic and Soft computing, 19–31, Kluwer Academic Publishers, Boston an extension of Logic Programming has been proposed. Logic programs on function-free languages are considered, and approximate and imprecise information are represented by introducing a similarity relation ? in the set of predicate names and object names of the language. The inference system exploits the classical resolution rule of the Logic Programming paradigm. Moreover, the notion of fuzzy least Herbrand model is also provided. In this paper, by introducing the general notion of structural translation of languages, we generalize these results to the case of logic programs with function symbols. Some properties of the similarity relations are also proven. 相似文献
8.
约束逻辑程序设计综述 总被引:1,自引:0,他引:1
一、引言 约束逻辑程序设计(Constraint Logic Program-ming.CLP)是基于人工智能(AI)中约束满足问题(Constraint Satisfaction Problem.CSP)模型的一种程序设计风范。CLP是逻辑程序设计(LP)的一种推广,是八十年代发展起来的一种新的逻辑程序设计方法。由于它继承了LP简单易懂的说明性描述方法并结合了CSP在求解问题时的效率,使它在解决很多AI问题(如组合问题、资源分配、事务安排等)时有不凡的表现。更由于AI领域中绝大多数问题可以用CLP来表示,所以这一方法已引起了人们的广泛注意,并在八十年代后期得以迅速发展。 相似文献
9.
提出了一种新的约束归纳逻辑程序设计方法。该方法能够与自顶向下的归纳逻辑程序设计系统结合,通过在自顶向下归纳方法的一步特殊化操作中引入Fisher判别分析等方法,使得系统能够导出不受变量个数限制的多种形式的线性约束,在不需要用户诱导,不依赖约束求解器的情况下,学习出覆盖正例而排斥负例的含约束的Horn子句程序。 相似文献
10.
Inductive logic programming (ILP) is concerned with the induction of logic programs from examples and background knowledge.
In ILP, the shift of attention from program synthesis to knowledge discovery resulted in advanced techniques that are practically
applicable for discovering knowledge in relational databases. This paper gives a brief introduction to ILP, presents selected
ILP techniques for relational knowledge discovery and reviews selected ILP applications.
Nada Lavrač, Ph.D.: She is a senior research associate at the Department of Intelligent Systems, J. Stefan Institute, Ljubljana, Slovenia (since
1978) and a visiting professor at the Klagenfurt University, Austria (since 1987). Her main research interest is in machine
learning, in particular inductive logic programming and intelligent data analysis in medicine. She received a BSc in Technical
Mathematics and MSc in Computer Science from Ljubljana University, and a PhD in Technical Sciences from Maribor University,
Slovenia. She is coauthor of KARDIO: A Study in Deep and Qualitative Knowledge for Expert Systems, The MIT Press 1989, and
Inductive Logic Programming: Techniques and Applications, Ellis Horwood 1994, and coeditor of Intelligent Data Analysis in
Medicine and Pharmacology, Kluwer 1997. She was the coordinator of the European Scientific Network in Inductive Logic Programming
ILPNET (1993–1996) and program cochair of the 8th European Machine Learning Conference ECML’95, and 7th International Workshop
on Inductive Logic Programming ILP’97.
Sašo Džeroski, Ph.D.: He is a research associate at the Department of Intelligent Systems, J. Stefan Institute, Ljubljana, Slovenia (since 1989).
He has held visiting researcher positions at the Turing Institute, Glasgow (UK), Katholieke Universiteit Leuven (Belgium),
German National Research Center for Computer Science (GMD), Sankt Augustin (Germany) and the Foundation for Research and Technology-Hellas
(FORTH), Heraklion (Greece). His research interest is in machine learning and knowledge discovery in databases, in particular
inductive logic programming and its applications and knowledge discovery in environmental databases. He is co-author of Inductive
Logic Programming: Techniques and Applications, Ellis Horwood 1994. He is the scientific coordinator of ILPnet2, The Network
of Excellence in Inductive Logic Programming. He was program co-chair of the 7th International Workshop on Inductive Logic
Programming ILP’97 and will be program co-chair of the 16th International Conference on Machine Learning ICML’99.
Masayuki Numao, Ph.D.: He is an associate professor at the Department of Computer Science, Tokyo Institute of Technology. He received a bachelor
of engineering in electrical and electronics engineering in 1982 and his Ph.D. in computer science in 1987 from Tokyo Institute
of Technology. He was a visiting scholar at CSLI, Stanford University from 1989 to 1990. His research interests include Artificial
Intelligence, Global Intelligence and Machine Learning. Numao is a member of Information Processing Society of Japan, Japanese
Society for Artificial Intelligence, Japanese Cognitive Science Society, Japan Society for Software Science and Technology
and AAAI. 相似文献
11.
This paper outlines a logic programming methodology which applies standardized logic program recursion forms afforded by a system of general purpose recursion schemes. The recursion schemes are conceived of as quasi higher-order predicates which accept predicate arguments, thereby representing parameterized program modules. This use of higher-order predicates is analogous to higher-order functionals in functional programming. However, these quasi higher-order predicates are handled by a metalogic programming technique within ordinary logic programming. Some of the proposed recursion operators are actualizations of mathematical induction principles (e.g. structural induction as generalization of primitive recursion). Others are heuristic schemes for commonly occurring recursive program forms. The intention is to handle all recursions in logic programs through the given repertoire of higher-order predicates. We carry out a pragmatic feasibility study of the proposed recursion operators with respect to the corpus of common textbook logic programs. This pragmatic investigation is accompanied with an analysis of the theoretical expressivity. The main theoretical results concerning computability are
- Primitive recursive functions can be re-expressed in logic programming by predicates defined solely by non-recursive clauses augmented with afold recursion predicate akin to the fold operators in functional programming.
- General recursive functions can be re-expressed likewise sincefold allows re-expression of alinrec recursion predicate facilitating linear, unbounded recursion.
12.
This paper presents a novel revision of the framework of Hybrid Probabilistic Logic Programming, along with a complete semantics
characterization, to enable the encoding of and reasoning about real-world applications. The language of Hybrid Probabilistic
Logic Programs framework is extended to allow the use of non-monotonic negation, and two alternative semantical characterizations
are defined: stable probabilistic model semantics and probabilistic well-founded semantics. These semantics generalize the
stable model semantics and well-founded semantics of traditional normal logic programs, and they reduce to the semantics of
Hybrid Probabilistic Logic programs for programs without negation. It is the first time that two different semantics for Hybrid
Probabilistic Programs with non-monotonic negation as well as their relationships are described. This proposal provides the
foundational grounds for developing computational methods for implementing the proposed semantics. Furthermore, it makes it
clearer how to characterize non-monotonic negation in probabilistic logic programming frameworks for commonsense reasoning.
An erratum to this article can be found at 相似文献
13.
Hypotheses constructed by inductive logic programming (ILP) systems are finite sets of definite clauses. Top-down ILP systems
usually adopt the following greedy clause-at-a-time strategy to construct such a hypothesis: start with the empty set of clauses
and repeatedly add the clause that most improves the quality of the set. This paper formulates and analyses an alternative
method for constructing hypotheses. The method, calledcautious induction, consists of a first stage, which finds a finite set of candidate clauses, and a second stage, which selects a finite subset
of these clauses to form a hypothesis. By using a less greedy method in the second stage, cautious induction can find hypotheses
of higher quality than can be found with a clause-at-a-time algorithm. We have implemented a top-down, cautious ILP system
called CILS. This paper presents CILS and compares it to Progol, a top-down clause-at-a-time ILP system. The sizes of the
search spaces confronted by the two systems are analysed and an experiment examines their performance on a series of mutagenesis
learning problems.
Simon Anthony, BEng.: Simon, perhaps better known as “Mr. Cautious” in Inductive Logic Programming (ILP) circles, completed a BEng in Information
Engineering at the University of York in 1995. He remained at York as a research student in the Intelligent Systems Group.
Concentrating on ILP, his research interests are Cautious Induction and developing number handling techniques using Constraint
Logic Programming.
Alan M. Frisch, Ph.D.: He is the Reader in Intelligent Systems at the University of York (UK), and he heads the Intelligent Systems Group in the
Department of Computer Science. He was awarded a Ph. D. in Computer Science from the University of Rochester (USA) in 1986
and has held faculty positions at the University of Sussex (UK) and the University of Illinois at Urbana-Champaign (USA).
For over 15 years Dr. Frisch has been conducting research on a wide range of topics in the area of automated reasoning, including
knowledge retrieval, probabilistic inference, constraint solving, parsing as deduction, inductive logic programming and the
integration of constraint solvers into automated deduction systems. 相似文献
14.
Veena S. Mellarkod Michael Gelfond Yuanlin Zhang 《Annals of Mathematics and Artificial Intelligence》2008,53(1-4):251-287
We introduce a knowledge representation language ${\cal AC(C)}$ extending the syntax and semantics of ASP and CR-Prolog, give some examples of its use, and present an algorithm, $\mathcal{AC}\!solver$ , for computing answer sets of ${\cal AC(C)}$ programs. The algorithm does not require full grounding of a program and combines “classical” ASP solving methods with constraint logic programming techniques and CR-Prolog based abduction. The ${\cal AC(C)}$ based approach often allows to solve problems which are impossible to solve by more traditional ASP solving techniques. We believe that further investigation of the language and development of more efficient and reliable solvers for its programs can help to substantially expand the domain of applicability of the answer set programming paradigm. 相似文献
15.
Regulations are pervasive in information systems. They manifest themselves as design rules, integrity constraints, deadlines, conventions, information disclosure requirements, policies, procedures, contracts, taxes, quotas and other statutes. Managing regulations is difficult. Regulations are complex, change frequently and rest on models of the real world that involve unusual vocabulary if not unusual concepts. Consequently, checking compliance with regulations is tedious and error-prone. Logic programming appears to provide a good framework for developing regulation management systems. Besides permitting arbitrary regulations to be modelled, it offers rapidity and ease of development, readability, incremental modifiability, extensibility and portability. These features are not provided by existing DP programming tools, database managers or conventional expert-system shells. This paper investigates the application of logic programming in a significant regulation management application: Workers' Compensation Insurance premium auditing. The insurance premium computation rules for the State of California were encoded as a large Prolog program. This application illustrates specific strengths and weaknesses of logic programming and Prolog in dealing with large-scale real-world regulations. 相似文献
16.
F.J. Lpez-Fraguas J. Snchez-Hernndez 《Electronic Notes in Theoretical Computer Science》2003,86(3):123
Constructive failure has been proposed recently as a programming construct useful for functional logic programming, playing a role similar to that of constructive negation in logic programming. On the other hand, almost any functional logic program requires the use of some kind of equality test between expressions. We face in this work in a rigorous way the interaction of failure and equality (even for non-ground expressions), which is a non trivial issue, requiring in particular the use of disequality conditions at the level of the operational mechanism of constructive failure. As an interesting side product, we develop a novel treatment of equality and disequality in functional logic programming, by giving them a functional status, which is better suited for practice than previous proposals. 相似文献
17.
Stefania Costantini Ottavio D'Antona Alessandro Provetti 《Information Processing Letters》2002,84(5):241-249
Logic programs under Answer Sets semantics can be studied, and actual computation can be carried out, by means of representing them by directed graphs. Several reductions of logic programs to directed graphs are now available. We compare our proposed representation, called Extended Dependency Graph, to the Block Graph representation recently defined by Linke [Proc. IJCAI-2001, 2001, pp. 641-648]. On the relevant fragment of well-founded irreducible programs, extended dependency and block graph turns out to be isomorphic. So, we argue that graph representation of general logic programs should be abandoned in favor of graph representation of well-founded irreducible programs, which are more concise, more uniform in structure while being equally expressive. 相似文献
18.
We give a framework for developing the least model semantics, fixpoint semantics, and SLD-resolution calculi for logic programs in multimodal logics whose frame restrictions consist of the conditions of seriality (i.e. ) and some classical first-order Horn clauses. Our approach is direct and no special restriction on occurrences of □i and i is required. We apply our framework for a large class of basic serial multimodal logics, which are parameterized by an arbitrary combination of generalized versions of axioms T, B, 4, 5 (in the form, e.g. 4:□i→□j□k) and I:□i→□j. Another part of the work is devoted to programming in multimodal logics intended for reasoning about multidegree belief, for use in distributed systems of belief, or for reasoning about epistemic states of agents in multiagent systems. For that we also use the framework, and although these latter logics belong to the mentioned class of basic serial multimodal logics, the special SLD-resolution calculi proposed for them are more efficient. 相似文献
19.
Slicing is a program analysis technique originally developed for imperative languages. It facilitates understanding of data flow and debugging.This paper discusses slicing of Constraint Logic Programs. Constraint Logic Programming (CLP) is an emerging software technology with a growing number of applications. Data flow in constraint programs is not explicit, and for this reason the concepts of slice and the slicing techniques of imperative languages are not directly applicable.This paper formulates declarative notions of slice suitable for CLP. They provide a basis for defining slicing techniques (both dynamic and static) based on variable sharing. The techniques are further extended by using groundness information.A prototype dynamic slicer of CLP programs implementing the presented ideas is briefly described together with the results of some slicing experiments. 相似文献
20.
We present a compositional model-theoretic semantics for logic programs, where the composition of programs is modelled by
the composition of the admissible Herbrand models of the programs. An Herbrand model is admissible if it is supported by the
assumption of a set of hypotheses. On one hand, the hypotheses supporting a model correspond to an open interpretation of
the program intended to capture possible compositions with other programs. On the other hand, admissible models provide a
natural model-theory for a form of hypothetical reasoning, called abduction. The application of admissibel models to programs
with negation is discussed.
Antonio Brogi: Dipartimento di Informatica, Università di Pisa, Corso Italia 40, 56125 Pisa, ItalyResearch interests: Programming Language Design and Semantics, Logic Programming and Artificial Intelligence 相似文献