Applying Logic Programming to Knowledge Discovery on the Internet

LP (Logic Programming) has been successfully applied to knowledge discovery in many fields. The execution of the LP is based on the evaluation of the first order predicate. Usually the information involved in the predicates are local and homogenous, thus the evaluation process is relatively simple. However, the evaluation process become much more complicated when applied to KDD on the Internet where the information involved in the predicates maybe heterogeneous and distributed over many different sits. Therefor, we try to attack the problem in a multi agent system's framework so that the logic program can be written in a site independent style and deal easily with heterogeneous represented information.

A Framed Temporal Logic Programming Language

We discuss the projection temporal logic (PTL), based on a primitiveprojection operator, prj. A framing technique is also presented, using which a synchronizationoperator, await, is defined within the underlying logic. A framed temporal logic programminglanguage (FTLL) is presented. To illustrate how to use both the language and framing technique, someexamples are given.

Agent-Oriented Probabilistic Logic Programming

Currently, agent-based computing is an active research area, and great efforts have been made towards the agent-oriented programming both from a theoretical and practical view. However, most of them assume that there is no uncertainty in agents＇ mental state and their environment. In other words, under this assumption agent developers are just allowed to specify how his agent acts when the agent is 100% sure about what is true/false. In this paper, this unrealistic assumption is removed and a new agent-oriented probabilistic logic programming language is proposed, which can deal with uncertain information about the world. The programming language is based on a combination of features of probabilistic logic programming and imperative programming.

A sequential model of bargaining in logic programming

This paper proposes a sequential model of bar- gaining specifying reasoning processes of an agent be- hind bargaining procedures. We encode agents＇ background knowledge, demands, and bargaining constraints in logic pro- grams and represent bargaining outcomes in answer sets. We assume that in each bargaining situation, each agent has a set of goals to achieve, which are normally unachievable with- out an agreement among all the agents who are involved in the bargaining. Through an alternating-offers procedure, an agreement among bargaining agents may be reached by ab- ductive reasoning. We show that the procedure converges to a Nash equilibrium if each agent makes rational offers/counter- offers in each round. In addition, the sequential model also has a number of desirable properties, such as mutual commit- ments, individual rationality, satisfactoriness, and honesty.

A New Integrated System of Logic Programming and Relational Database

Based on the study of the current two methods—interpretation and compilation—for the integration of logic programming and relational database,a new precompilation-based interpretive approach is proposed.It inherits the advantages of both methods,but overcomes the drawbacks of theirs.A new integrated system based on this approach is presented,which has been implemented on Micro VAX Ⅱ and applied to practise as the kernel of the GKBMS knowledge base management system.Also discussed are the key implementation techniques,including the coupling of logic and relational database systems,the compound of logic and relational database languages,the partial evaluation and static optimization of user's programs,fact scheduling and version management in problem-solving.

An Implementation of Pure Horn Clause Logic Programming in a Reduction System

Many reduction systems have been presented for implementing functional programming languages. We propose here an extension of a reduction architecture to realize a kind of logic programming——pure Horn clause logic programming.This is an attempt to approach amalgama- tion of the two important programming paradigms.

MSVL： a typed language for temporal logic programming

The development of types is an important but challenging issue in temporal logic programming. In this paper, we investigate how to formalize and implement types in the temporal logic programming language MSVL, which is an executable subset of projection temporal logic （PTL）. Specifically, we extend MSVL with a few groups of types including basic data types, pointer types and struct types. On each type, we specify the domain of values and define some standard operations in terms of logic functions and predicates. Then, it is feasible to formalize statements of type declaration of program variables and statements of struct definitions as logic formulas. As the implementation of the theory, we extend the MSV toolkit with the support of modeling, simulation and verification of typed MSVL programs. Applications to the construction of AVL tree and ordered list show the practicality of the language.

Symmetric Structure in Logic Programming

It is argued that some symmetric structure in logic programs could be taken into account when implementing semantics in logic programming. This may enhance the declarative ability or expressive power of the semantics. The work presented here may be seen as representative examples along this line. The focus is on the derivation of negative information and some other classic semantic issues. We first define a permutation group associated with a given logic program. Since usually the canonical models used to reflect the common sense or intended meaning are minimal or completed models of the program, we expose the relationships between minimal models and completed models of the original program and its so-called G-reduced form newlt-derived via the permutation group defined. By means of this G reduced form, we introduce a rule to assume negative information termed G-CWA, which is actually a generalization of the GCWA. We also develop the notions of G-definite, G-hierarchical and G-stratified logic programs, which are more general than definite, hierarchical and stratified programs, and extend some well-known declarative and procedural semantics to them, respectively. Keywords symmetry - logic programming - semantics Partially supported by the National Natural Science Foundation of China under Grant No.60373113.Jin-Zhao Wu was born in 1965. He obtained his Ph.D. degree in 1994 from the Institute of Systems Science, the Chinese Academy of Sciences. From 1994 to 1999 he was a post-doctoral and research scientist in Peking University and Max-Planck Institute of Computer Science. Since 2000 he has been working on the Faculty of Mathematics and Computer Science, University of Mannheim.Harald Fecher was born in 1972. He obtained his Ph.D. degree in 2003 from the Faculty of Mathematics and Computer Science, University of Mannheim. Since 2004 he has been research scientist in the Faculty of Computer Science, University of Kiel.

Identification of Tumor Evolution Patterns by Means of Inductive Logic Programming

In considering key events of genomic disorders in the development and progression of cancer, the correlation between genomic instability and carcinogenesis is currently under investigation. In this work, we propose an inductive logic programming approach to the problem of modeling evolution patterns for breast cancer. Using this approach, it is possible to extract fingerprints of stages of the disease that can be used in order to develop and deliver the most adequate therapies to patients. Furthermore, such a model can help physicians and biologists in the elucidation of molecular dynamics underlying the aberrations-waterfall model behind carcinogenesis. By showing results obtained some hints about further approach to the hypotheses. on a real-world dataset, we try to give knowledge-driven validations of such

IMPLEMENTATION OF 3-VALUED PARACONSISTENT LOGIC PROGRAMMING TOWARDS DECISION MAKING SYSTEM OF AGENTS

Due to the rapid development of applications of artificial intelligence and robotics in recent years, the necessity of reasoning and decision making with uncertain and inaccurate information is increasing. Since robots in the real world are always exposed to behavioral inaccuracies and uncertainty arising from recognition methods, they may occasionally encounter contradictory facts during reasoning on action decision. Paraconsistent logic programming is promising to make appropriate action decisions even when an agent is exposed to such uncertain information or contradictory facts, but there has been no implementation of this programming to the best of our knowledge. We propose a resolution algorithm for the 3-valued paraconsistent logic programming system QMPT0 and its implementation on SWI-Prolog. We also describe an application of the 3-valued paraconsistent logic programming regarding agent decision making.

On the Complexities of Non-Horn Clause Logic Programming

There have been active work to extend the Prolog style Horn Clause logic programming to non-Horn clauses.In this paper,we will analyze the complexities of several such extensions.The purpose is to understand the computational complexity of these inference systems.The analyses do not prove that any one system is better than the others all the time.But they do suggest that one system may be better than the others for some particular problems.We also discuss the effect of caching.

Programming Logic Modeling and Cross-Program Defect Detection Method for Object-Oriented Code

Code defects can lead to software vulnerability and even produce vulnerability risks.Existing research shows that the code detection technology with text analysis can judge whether object-oriented code files are defective to some extent.However,these detection techniques are mainly based on text features and have weak detection capabilities across programs.Compared with the uncertainty of the code and text caused by the developer’s personalization,the programming language has a stricter logical specification,which reflects the rules and requirements of the language itself and the developer’s potential way of thinking.This article replaces text analysis with programming logic modeling,breaks through the limitation of code text analysis solely relying on the probability of sentence/word occurrence in the code,and proposes an object-oriented language programming logic construction method based on method constraint relationships,selecting features through hypothesis testing ideas,and construct support vector machine classifier to detect class files with defects and reduce the impact of personalized programming on detection methods.In the experiment,some representative Android applications were selected to test and compare the proposed methods.In terms of the accuracy of code defect detection,through cross validation,the proposed method and the existing leading methods all reach an average of more than 90%.In the aspect of cross program detection,the method proposed in this paper is superior to the other two leading methods in accuracy,recall and F1 value.

Ethical Decision-Making Framework Based on Incremental ILP Considering Conflicts

Humans are experiencing the inclusion of artificial agents in their lives,such as unmanned vehicles,service robots,voice assistants,and intelligent medical care.If the artificial agents cannot align with social values or make ethical decisions,they may not meet the expectations of humans.Traditionally,an ethical decision-making framework is constructed by rule-based or statistical approaches.In this paper,we propose an ethical decision-making framework based on incremental ILP(Inductive Logic Programming),which can overcome the brittleness of rule-based approaches and little interpretability of statistical approaches.As the current incremental ILP makes it difficult to solve conflicts,we propose a novel ethical decision-making framework considering conflicts in this paper,which adopts our proposed incremental ILP system.The framework consists of two processes:the learning process and the deduction process.The first process records bottom clauses with their score functions and learns rules guided by the entailment and the score function.The second process obtains an ethical decision based on the rules.In an ethical scenario about chatbots for teenagers’mental health,we verify that our framework can learn ethical rules and make ethical decisions.Besides,we extract incremental ILP from the framework and compare it with the state-of-the-art ILP systems based on ASP(Answer Set Programming)focusing on conflict resolution.The results of comparisons show that our proposed system can generate better-quality rules than most other systems.

Concurrent Constraint Programming:A Language and Its Execution Model

To overcome inefficiency in traditional logic programming, a declarative programming language COPS is designed based on the notion of concurrent constraint programming (CCP). The improvement is achieved by the adoption of constraint-based heuristic strategy and the introduction of deterministic components in the framework of CCP. Syntax specification and an operational semantic description are presented.

Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms

Radial Basis Function Neural Network(RBFNN)ensembles have long suffered from non-efficient training,where incorrect parameter settings can be computationally disastrous.This paper examines different evolutionary algorithms for training the Symbolic Radial Basis Function Neural Network(SRBFNN)through the behavior’s integration of satisfiability programming.Inspired by evolutionary algorithms,which can iteratively find the nearoptimal solution,different Evolutionary Algorithms(EAs)were designed to optimize the producer output weight of the SRBFNN that corresponds to the embedded logic programming 2Satisfiability representation(SRBFNN-2SAT).The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms,including Genetic Algorithm(GA),Evolution Strategy Algorithm(ES),Differential Evolution Algorithm(DE),and Evolutionary Programming Algorithm(EP).Each of these methods is presented in the steps in the flowchart form which can be used for its straightforward implementation in any programming language.With the use of SRBFNN-2SAT,a training method based on these algorithms has been presented,then training has been compared among algorithms,which were applied in Microsoft Visual C++software using multiple metrics of performance,including Mean Absolute Relative Error(MARE),Root Mean Square Error(RMSE),Mean Absolute Percentage Error(MAPE),Mean Bias Error(MBE),Systematic Error(SD),Schwarz Bayesian Criterion(SBC),and Central Process Unit time(CPU time).Based on the results,the EP algorithm achieved a higher training rate and simple structure compared with the rest of the algorithms.It has been confirmed that the EP algorithm is quite effective in training and obtaining the best output weight,accompanied by the slightest iteration error,which minimizes the objective function of SRBFNN-2SAT.

A temporal programming model with atomic blocks based on projection temporal logic

Atomic blocks, a high-level language construct that allows programmers to explicitly specify the atomicity of operations without worrying about the implementations, are a promising approach that simplifies concurrent programming. On the other hand, temporal logic is a successful model in logic programming and concurrency verification, but none of existing temporal programming models supports concurrent programming with atomic blocks yet. In this paper, we propose a temporal programming model （αPTL） which extends the projection temporal logic （PTL） to support concurrent programming with atomic blocks. The novel construct that formulates atomic execution of code blocks, which we call atomic interval formulas, is always interpreted over two consecutive states, with the internal states of the block being abstracted away. We show that the framing mechanism in projection temporal logic also works in the new model, which consequently supports our development of an executive language. The language supports concurrency by introducing a loose interleaving semantics which tracks only the mutual exclusion between atomic blocks. We demonstrate the usage of αPTL by modeling and verifying both the fine-grained and coarse-grained concurrency.

An Approach for Handling Conflicts in Authorization

Based on logic programs, authorization conflicts and resolution strategies are analyzed through the explanation of some examples on the health care sector. A resolution scheme for handling conflicts in high level authorization specification by using logic program with ordered disjunction （LPOD） is proposed. The scheme is useful for solving conflicts resulted from combining positive and negative authorization, complexity of authorization management, and less clarity of the specification. It can well specify kinds of conflicts （such as exceptional conflicts, potential conflicts）, and is based on literals and dependent contexts. Thus it is expressive and available. It is shown that authorizations based on rules LPOD is very important both in theory and practice.

An Open Environment for Cooperative Equational Solving

We describe a system called CFLP which aims at the integration of the best features of functional logic programming (FLP), cooperative constraint solving (CCS), and distributed computing. FLP provides support for defining one's own abstractions over a constraint domain in an easy and comfortable way, whereas CCS is employed to solve systems of mixed constraints by iterating specialized constraint solving methods in accordance with a well defined strategy. The system is a distributed implementation of a cooperative constraint functional logic programming scheme that combines higher order lazy narrowing with cooperative constraint solving. The model takes advantage of the existence of several constraint solving resources located in a distributed environment (e.g., a network of computers), which communicate asynchronously via message passing. To increase the openness of the system, we are redesigning CFLP based on CORBA. We discuss some design and implementation issues of the system.

A characterization of answer sets for logic programs

Checking if a program has an answer set, and if so, compute its answer sets are just some of the important problems In answer set logic progremming. Solving these problems using Gelfond and Llfschltz＇s original definition of answer sets Is not an easy task. Alternative charaoterlzatlons of answer sets for nested logic programs by Erdem and Llfschltz, Lee and Llfschltz, and You at el. are based on the completion semantics and various notions of tlghtnese. However, the notion of tightness Is a local notion In the sense that for different answer sets there are, In general, different level mappings capturing their tlghtnese. This makes It hard to be used In the deelgn of algorithms for computing answer sets. This paper proposes a charecterization of answer sets based on sets of generetlng rules. From this charaoterlzation new algorithms are derived for computing answer sets and for performing some other reasoning teaks. As an application of the charecterlzatlon a sufficient and necessary condition for the equivalence between answer set sementics and completion semantics has been proven, and a basic theorem Is shown on computing answer sets for nested logic programs baaed on an extended notion of loop formulas. These results on tlghtnese and loop formulas are more general than that in You and Lin＇a work.

SCKE:Combining Logic- with Object-Oriented Paradigm

A new implementation(SCKE—Stractured Communication Knowledge Entity)has been proposed towards combining the logic-with the object-oriented paradigm of computing.It is intended to explore the advantages in these two paradigms in a structured,natural and efficient manner for large-scale know- ledge processing.The SCKE model supports modularity and protection for the structured development of knowledge systems.It also introduces the concepts that are typical for the object-oriented systems in the logic-oriented paradigm,without losing its advantages as a declarative language.Various inheritance hier- archies are supported in the SCKE model.They provide the semantics basis for various knowledge in AI systems.The M-entity/K-entity/Instance inheritance captures the relationship among the control, procedural and factual knowledge in AI systems,And,the super-entity/entity/instance inheritance shows the concepts of data abstraction in the knowledge of a particular domain.In addition,the SCKE model is not simply supported on top of Prolog like other attempts to integrate the object-into the log- ic-oriented paradigm.The SCKE model is a tighltly coupled model of the logic-and the object-oriented paradigm and its interpreter uniformly interprets the logic semantics and the object-oriented semantics.