A formal definition and a sound implementation of analogical reasoning in logic programming

One of the modern paradigms to develop an application is object oriented analysis and design. In this paradigm, there are several objects and each object plays some specific roles in applications. In an application, we must distinguish between procedural semantics and declarative semantics for their implementation in a specific programming language. For the procedural semantics, we can write a set of instructions that must be executed sequentially. The declarative semantics declare a set of facts and rules. They do not specify the sequence of steps for doing the processing. In this paper, we present four taxonomies for the rules in object-oriented paradigm and discuss how the paradigm can be extended to support declarative semantic of applications. Then, the rules in the taxonomies are evaluated in four case studies. After that, an approach is recommended for finding and implementation of declarative semantics, based on some practical experience obtained from the evaluation.

A meta-program, regardless of the nature of the programming language, is a program whose data denotes another (object) program. The importance of meta-programming can be gauged from its large number of applications. These include compilers, interpreters, program analysers, and program transformers. Furthermore, if the object program is a logic or functional program formalizing some knowledge, then the meta-program may be regarded as a meta-reasoner for reasoning about this knowledge. In this chapter, the meta-program is assumed to be a logic program. The object program does not have to be a logic program although much of the work in this chapter assumes this. We have identified three major topics for consideration. These are the theoretical foundations of meta-programming, the suitability of the alternative meta-programming techniques for different applications, and methods for improving the efficiency of meta-programs. As with logic programs generally, meta-programs have declarative and procedural semantics. The theoretical study of meta-programming shows that both aspects of the semantics depend crucially on the manner in which object programs are represented as data in a meta-program. The second theme of the paper is the problem of designing and choosing appropriate ways of specifying important meta-programming problems, including dynamic metaprogramming and problems involving self-application. The third theme concerns efficient implementation of meta-programs. Meta-programming systems require representations with facilities that minimize the overhead of interpreting the object program. In addition, efficiency can be gained by transforming the meta-program, specializing it for the particular object program it is reasoning about. This chapter, which concentrates on these aspects of meta-programming, is not intended to be a survey of the field. A more complete survey of meta-programming for logic programming can be found in [Barklund, 1995]. Many issues in meta-programming have their roots in problems in logic which have been studied for several decades. This chapter emphasizes meta-programming solutions. It is not intended to give a full treatment of the underlying logical problems, though we try to indicate some connections to wider topics in meta-logic. The meta-programs in this chapter are logic programs based on first order logic.

The PPL framework is proposed as a simple extension to logic programming aiming at handling resources. It is argued that the separation between logical treatments and resource handling is desirable and, to that end, resources are proposed to be manipulated by means of pre- and post-conditions associated with usual Horn clauses. The expressiveness of the resulting framework is evidenced through the coding of several applications involving objects, databases, actions and changes. Operational and declarative semantics are presented as well. The operational semantics rests on a derivation relation stating how goals and conditions are evaluated. The declarative semantics extends the classical model and fixed-point theories to take into account the evaluation of pre- and post-conditions, and in particular the non-monotonic behavior of the world of resources they induce in general. As suggested, an effort has been made to keep the work close to the classical logic programming setting. In particular, the semantics are in the main streams of logic programming semantics. However, the PPL framework raises new problems for which fresh solutions are proposed.

Active Logic is a conceptual system, the principles of which are satisfied with formalisms of reasoning, which allow correlating the results of reasoning with moments in time and ensuring tolerance to contradictions. At present, tolerance to contradictions (paraconsistency) as applied to Active Logic systems has received theoretical justification in the works of the authors of this report and refers to the so-called formalisms of step theories, combining the principles of Active Logic and logical programming. In particular, it was proved that the argumentative semantics of the formalism of extended step theories, which have two types of negation and have more developed expressive capabilities, are paranormal. The formalism introduced in this paper has even greater expressive capabilities. Keeping all the controls for the process of reasoning in time, this formalism allows one to more adequately represent facts about the subject area by using the language of first-order logic instead of the language of propositional logic. For the formalism of extended step theories of the first order, a declarative semantics is proposed, its paraneosistance is shown, and the expressive possibilities of this formalism in relation to the tasks of action planning are demonstrated using the example of the monkey and the banana.KeywordsActive logicTime reasoningExtended first-order step theoriesDeclarative semanticsParaconsistencyArgumentative semantics

In this work in progress, we develop a program analysis capable of efficiently detecting duplicated functionality within a logic program or a set of logic programs. Our main motivation is to provide an analysis that allows to automatically spot those locations in a program where a transformation could be applied that removes the duplication from the source code.KeywordsSource CodeLogic ProgramInput StringLonge Common SubsequenceLonge Common SubsequenceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Most of the theoretical work on the semantics of logic programs assumes an interpreter that provides a complete resolution procedure. In contrast, for reasons of efficiency, most logic programming languages are built around incomplete procedures. This difference is rooted in Prolog, which evaluates resolvent trees in a depth-first rather than a breadth-first order. The gap is widened by some equational logic languages, which combine the incompleteness of depth-first evaluation with incomplete approximations to equational unification. Because of this gap, it is unsound to reason about logic programs using their declarative semantics. This in turn makes it difficult to develop abstraction mechanisms that can be used to partition a logic program into independently specifiable modules.

We are now touching a problem how we add soft computing aspects to logic programming and we have been discussing null attribute values on logic programs. Here, we introduce two functors setu and sets into logic programs for describing indefinite attribute values explicitly. Every logic program with setu or sets has variability and tolerance in itself, namely this program expresses a set of possible definite logic programs. We call this program a variational logic program. In this paper, we show the variational logic programs and a theorem prover for them.

A Declarative Approach to Business Rules in Contracts: Courteous Logic Programs in XML

Lawry's label semantics for modeling and computing with linguistic information in natural language provides a clear interpretation of linguistic expressions and thus a transparent model for real-world applications. Meanwhile, annotated logic programs (ALPs) and its fuzzy extension AFLPs have been developed as an extension of classical logic programs offering a powerful computational framework for handling uncertain and imprecise data within logic programs. This paper proposes annotated linguistic logic programs (ALLPs) that embed Lawry's label semantics into the ALP/AFLP syntax, providing a linguistic logic programming formalism for development of automated reasoning systems involving soft data as vague and imprecise concepts occurring frequently in natural language. The syntax of ALLPs is introduced, and their declarative semantics is studied. The ALLP SLD-style proof procedure is then defined and proved to be sound and complete with respect to the declarative semantics of ALLPs. © 2010 Wiley Periodicals, Inc.

The problem of determining the correct declarative semantics for generalized logic programs is still open. In generalized logic programs the body of a rule may contain negated goals. Using a logical equivalence these programs may be viewed as disjunctive logic programs where the head of a rule may contain a disjunction of goals. We hope that a careful study of the declarative semantics of disjunctive logic programs will produce criteria for evaluating the different candidates for the semantics of generalized logic programs.A conceptual analysis leads to a semantical definition of the notion of a disjunctive deductive database as a generalization of the notion of a deductive database. It will be shown that the notion of a disjunctive deductive database is equivalent to the syntactical definition of a disjunctive logic program. We have characterized disjunctive deductive databases, i. e. theories which admit in each irreducible component a minimal Herbrand model and for which this property is preserved under the addition of new facts, as disjunctive logic programs. As a special case the result yields the known characterization of deductive databases, i. e. theories which admit a minimal Herbrand model and for which this property is preserved under the addition of new facts, as logic programs. In the presence of equations term structures i. e. extended Herbrand structures replace the Herbrand structures and h-core models replace the minimal models. Actually, the results could be proved in a more general context where pseudo term structures replace the term structures. In addition, there is an intermediate case where the irreducible components coincide with the connected components. Moreover, there are characterization results for the cases where the uniformity condition is not present.KeywordsLogic ProgramIrreducible ComponentTerm StructureCanonical ModelDeductive DatabaseThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Deciding whether two code fragments are semantic clones, or type-4 clones, is a problem with many ramifications. Current research often focuses on the problem in an imperative or object-oriented setting and most existing work uses abstract syntax trees, program dependency graphs, program metrics or text-based, token-based and machine learning-based approaches to identify semantic clones. In this work, we adopt a fundamentally different point of view and express clone detection as a search problem in a logic programming setting. Due to their restricted syntax and semantics, (constraint) logic programs are by nature simple and elegant candidates for automated analysis. After having formalized the clone detection problem at the level of predicates, we develop a study of the different parameters that come into play in the resulting framework. We try and identify the complexity issues involved in a general semantic clone detection procedure that essentially computes so-called most specific generalizations for predicates written in constraint logic programming (CLP). Even though well-known for basic structures such as literals and terms, generalization (or anti-unification) of more complex structures such as clauses and predicates has received very little attention. We show that the anti-unification allows both to control the search and guide the detection of cloned predicates. We pinpoint where efficient approximations are needed in order to be able to identify semantic code clones in a manageable time frame.

We present declarative and procedural semantics for a deductive object-oriented language, Gulog. The declarative semantics is based on preferred minimal models. We describe both bottom-up and top-down query evaluation procedures and show that they are sound with respect to the declarative semantics. The results contribute to our understanding of the interaction of inheritance, overriding and deduction in the presence of both functional and set-valued methods, and multiple inheritance.

Background. Programming is widely known to be a cognitively demanding field. Learning programming can be a strenuous task without the proper guidance and methodology. Students often face difficulties in understanding even the most basic and fundamental concepts of programming, leading to their confusion and disappointment. Serious games for programming have the potential to alleviate students’ difficulties with programming. Aim. This article introduces a new serious game named jAVANT-GARDE which aims to educate the player on the basic concepts of programming and object-oriented programming through Java. By design, the game is suitable for everyone, even for players with no previous knowledge of programming. This article aims to present important information regarding the design, implementation and pilot evaluation of jAVANT-GARDE. Method. The game was evaluated by 42 high school students (age 16-17) in terms of perceived player experience and short-term learning. The participants played the game for one hour in the school lab and then answered a questionnaire based on the MEEGA+ framework. Results. Students evaluated positively the game in terms of its usability, confidence in playing the game, challenge, satisfaction, fun, focused attention and relevance. Moreover, the majority of students stated that would prefer learning programming with this game to learning through other teaching methods. Conclusions. The results of the pilot study and students’ replies in the questionnaire are rather positive. This gives us the initiative to proceed with studying the effect of the game in long-term learning of programming concepts.

We present a probabilistic logic programming framework that allows the representation of conditional probabilities. While conditional probabilities are the most commonly used method for representing uncertainty in probabilistic expert systems, they have been largely neglected by work in quantitative logic programming. We define a fixpoint theory, declarative semantics, and proof procedure for the new class of probabilistic logic programs. Compared to other approaches to quantitative logic programming, we provide a true probabilistic framework with potential applications in probabilistic expert systems and decision support systems. We also discuss the relationship between such programs and Bayesian networks, thus moving toward a unification of two major approaches to automated reasoning.

On the semantics of μ Log