描述逻辑εL混合循环术语集的LCS和MSC推理

分析了描述逻辑循环术语集的研究现状和存在的问题,在F.Baader工作的基础上进一步研究了描述逻辑εL混合循环术语集的LCS(least common subsumer)和MSC(most specific concept)推理问题.给出了εL混合循环术语集的语法和语义.针对εL混合循环术语集LCS和MSC推理的需要,提出了TBox-完全的概念,并重新定义了描述图.使用描述图和TBox-完全给出了最大不动点语义下εL混合循环术语集LCS和MSC的推理算法,证明了推理算法的正确性,并证明了推理算法是多项式时间复杂的.该推理算法为(L混合循环术语集的LCS和MSC推理提供了理论基础.     

描述逻辑εL循环术语集的混合推理

循环术语集是描述逻辑长期以来的研究难点,它最基本的问题即语义及推理问题没有得到合理的解决.分析了描述逻辑循环术语集的研究现状和存在的问题,在Baader和Brandt的基础上进一步研究了描述逻辑εL循环术语集的混合推理问题.给出了εL的混合循环知识库的语法和语义(包括不动点语义和描述语义).针对εL循环术语集混合推理的需要.提出了TBox-完全的概念,并重新定义了描述图(包括语法描述图和语义描述图).使用描述图之间的模拟关系和TBox-完全概念给出了最大不动点语义和描述语义下εL混合循环知识库的实例检测推理算法,证明了推理算法的正确性,并给出了推理算法的复杂性定理.     

带RVM的描述逻辑εL混合循环术语集的语义及推理

分析描述逻辑循环术语集的研究现状和存在的问题,在F.Baader和S.Brandt的基础上进一步研究带RVM的描述逻辑εL混合循环术语集的语义及推理问题.给出带RVM的εL混合循环术语集的语法和语义.针对带RVM的εL混合循环术语集包含推理的需要,提出TBox-完全的概念,并重新定义描述图,使用描述图之间的模拟关系和TBox-完全给出最大不动点语义和描述语义下带RVM的εL混合循环术语集的概念包含推理算法,证明推理算法的正确性,并证明推理算法是多项式时间复杂的.     

描述逻辑εLN 循环术语集的不动点语义及推理

循环术语集是描述逻辑长期以来的研究难点,其最基本的问题即语义及推理问题没有得到合理的解决.分析了描述逻辑循环术语集的研究现状和存在的问题,将Baader 的工作扩展到新的方向.针对更大的描述逻辑系统研究了循环术语集的语义及推理机制,即在描述逻辑εL 的基础上添加数量约束构造算子,提出了描述逻辑εLN,给出了εLN 的语义(包括不动点语义和描述语义).针对εLN 的需要,重新定义了描述图(包括语法描述图和语义描述图).使用描述图之间的模拟关系给出了不动点语义下εLN 循环术语集的可满足性和包含关系推理算法,并证明了推理算法是多项式时间复杂的.     

描述逻辑FL-循环术语集的语义及推理

循环术语集是描述逻辑长期以来的研究难点,它的最基本的问题即语义及推理问题没有得到合理的解决.文中分析了描述逻辑循环术语集的研究现状和存在的问题,在Baader的基础上进一步研究了描述逻辑FL~-循环术语集的语义及推理问题.给出了FL~-循环术语集的语法、语义和不动点模型的构造方法.针对FL~-循环术语集的需要,提出了一种新的有限自动机,使用有限自动机给出了不动点语义和描述语义下FL~-循环术语集的可满足性和包含推理算法,证明了推理算法的正确性,并给出了推理算法的复杂性定理.     

带n-元存在量词的描述逻辑MSC推理

分析了描述逻辑非标准推理的重要性,特别分析了描述逻辑MSC(Most Specific Concept)推理的研究现状和存在的问题.针对目前描述逻辑MSC推理不能处理n-元存在量词的不足,研究了带n-元存在量词的描述逻辑εL(n)的MSC推理问题.提出了一种新的εL(n)一描述图,利用描述树和描述图给出了描述逻辑εL(n)的MSC近似推理算法,并利用εL(n)-描述树嵌套和εL(n)-描述树描述图同态证明了MSC近似推理算法的正确性.作为一个附带的结果,利用εL(n)-描述树描述图同态给出了εL(n)-的实例推理算法,也证明了实例推理算法的正确性.     

带传递关系和存在量词的描述逻辑MSC推理

分析了描述逻辑非标准推理的重要性,特别分析了描述逻辑MSC推理的研究现状和存在的问题.针对目前描述逻辑MSC推理不能同时处理传递关系和存在量词的不足,研究了带传递关系和存在量词的描述逻辑εL+的MSC推理问题.提出了一种新的εL+-述图,利用描述树和描述图给出了描述逻辑εL+的MSC近似推理算法,并利用εL+-描述树同态和εL+-描述树描述图同态证明了MSC近似推理算法的正确性.作为一个附带的结果,利用εL+-描述树描述图同态给出了εL+的实例推理算法,也证明了实例推理算法的正确性.     

描述逻辑μALCIO的语义及推理

循环术语集是描述逻辑长期以来的研究难点,它的最基本的问题即语义及推理问题没有得到合理的解决.分析了描述逻辑循环术语集的研究现状和存在的问题,基于混合μ-演算将不动点构造算子引入到含有枚举构造算子的描述逻辑ALCIO中,提出了一种允许包含循环术语集的描述逻辑μALCIO.给出了μALCIO的语法和语义,证明了μALCIO的可满足性推理等价于混合μ-演算的可满足性推理,并利用树自动机理论给出了μALCIO的可满足性推理算法以及给出了推理算法正确性证明和复杂性定理.     

描述逻辑μALCQO 的语义及推理

循环术语集是描述逻辑长期以来的研究难点,其最基本的问题即语义及推理问题没有得到合理的解决.基于混合分级μ-演算将不动点构造算子引入到含有枚举构造算子的描述逻辑ALCQO 中,提出了一种允许包含循环术语集的描述逻辑μALCQO.给出了μALCQO 的语法、语义和不动点构造算子的性质,证明了μALCQO 的可满足性推理等价于混合分级μ-演算的可满足性推理.基于混合分级μ-演算可满足性推理算法,并利用完全强化自动机给出了μALCQO的可满足性推理算法,以及给出了推理算法正确性证明和复杂性定理.μALCQO为进一步给出同时含有不动点构造算子和枚举构造算子的表达能力强的描述逻辑推理算法提供了理论基础.     

描述逻辑非标准推理

描述逻辑是知识工程应用领域中重要的一类知识表示形式化工具。近年来,解决描述逻辑标准推理和非标准推理已成为描述逻辑研究的一个重要内容。文中概述描述逻辑的标准推理和非标准推理的重要性和研究进展,给出LCS推理、MSC推理、重写推理、匹配推理、调试推理和保守扩充等非标准推理的定义和实现这些推理的主要技术。深入讨论LCS推理、MSC推理和匹配推理,以及混合循环术语集的非标准推理及其研究进展。最后探讨描述逻辑非标准推理的发展趋向。     

Transfinite Semantics in the Form of Greatest Fixpoint

Transfinite semantics is a semantics according to which program executions can continue working after an infinite number of steps. Such a view of programs can be useful in the theory of program transformations.So far, transfinite semantics have been succesfully defined for iterative loops. This paper provides an exhaustive definition for semantics that enable also infinitely deep recursion.The definition is actually a parametric schema that defines a family of different transfinite semantics. As standard semantics also match the same schema, our framework describes both standard and transfinite semantics in a uniform way.All semantics are expressed as greatest fixpoints of monotone operators on some complete lattices. It turns out that, for transfinite semantics, the corresponding lattice operators are cocontinuous. According to Kleene’s theorem, this shows that transfinite semantics can be expressed as a limit of iteration which is not transfinite.     

Equivalence of formal semantics definition methods

There are numerous methods of formally defining the semantics of computer languages. Each method has been designed to fulfil a different purpose. For example, some have been designed to make reasoning about languages as easy as possible; others have been designed to be accessible to a large audience and some have been designed to ease implementation of languages. Given two semantics definitions of a language written using two separate semantics definition methods, we must be able to show that the two are in fact equivalent. If we cannot do this then we either have an error in one of the semantics definitions, or more seriously we have a problem with the semantics definition methods themselves.Three methods of defining the semantics of computer languages have been considered, i.e. Denotational Semantics, Structural Operational Semantics and Action Semantics. An equivalence between these three is shown for a specific example language by first defining its semantics using each of the three definition methods. The proof of the equivalence is then constructed by selecting pairs of the semantics definitions and showing that they define the same language.A full version of this paper can be accessed via our web page http://www.cs.man.ac.uk/fmethods/ facj.html     

多Agent信念逻辑及其在概率意义下的推广

首先建立了一种多Agent信念逻辑MBL(multi-agentbelieflogic),在经典信念逻辑基础上增加了普遍信念算子和公共信念算子,给出MBL的Kripke语义与广义Aumann语义,讨论了两者的等价性,证明了MBL对于上述两种语义的可靠性和完备性.其次,建立了一种多Agent概率信念逻辑MPBL(multi-agentprobabilisticbelieflogic),通过在广义Aumann语义基础上引入概率空间,给出了MPBL的概率Aumann语义,证明了它的可靠性,并给出MPBL的一些推论.     

A compact fixpoint semantics for term rewriting systems

This work is motivated by the fact that a “compact” semantics for term rewriting systems, which is essential for the development of effective semantics-based program manipulation tools (e.g. automatic program analyzers and debuggers), does not exist. The big-step rewriting semantics that is most commonly considered in functional programming is the set of values/normal forms that the program is able to compute for any input expression. Such a big-step semantics is unnecessarily oversized, as it contains many “semantically useless” elements that can be retrieved from a smaller set of terms. Therefore, in this article, we present a compressed, goal-independent collecting fixpoint semantics that contains the smallest set of terms that are sufficient to describe, by semantic closure, all possible rewritings. We prove soundness and completeness under ascertained conditions. The compactness of the semantics makes it suitable for applications. Actually, our semantics can be finite whereas the big-step semantics is generally not, and even when both semantics are infinite, the fixpoint computation of our semantics produces fewer elements at each step. To support this claim we report several experiments performed with a prototypical implementation.     

调用模式和正确调用模式语义在Prolog程序测试中的应用*

将基于调用模式语义和正确调用模式语义的程序分析技术应用于Prolog程序的CPM测试。通过调用模式分析获得内部过程被调用和成功调用的条件,利用前者删除不满足调用条件的测试帧,或当删除条件不满足时利用该条件更新测试规格中过程属性的划分准则;利用后者预测CPM测试的结果。该方法可较好地保持程序测试的质量,改善Prolog程序的CPM测试过程。     

Equivalence of queries that are sensitive to multiplicities

The query equivalence problem has been studied extensively for set-semantics and, more recently, for bag and bag-set semantics. However, SQL queries often combine set, bag and bag-set semantics. For example, an SQL query that returns a multiset of elements may call a subquery or view that returns a set of elements. Queries may access both relations that do not contain duplicates, as well as relations with duplicates. As another example, in SQL one can compute a multiset-union of queries, each of which returns a set of answers. This paper presents combined semantics, which formally models query evaluation combining set, bag and bag-set semantics. The equivalence problem for queries evaluated under combined semantics is studied. A sufficient condition for equivalence is presented. For several important common classes of queries necessary and sufficient conditions for equivalence are presented. An early version of this article appeared in [7]. This paper extends [7] to include bag semantics, in addition to set and bag-set semantics. This work was partially supported by the Israel Science Foundation (Grant 1032/05).     

There is no fully abstract fixpoint semantics for non-deterministic languages with infinite computations

It is well known that for many non-deterministic programming languages there is no continuous fully abstract fixpoint semantics. This is usually attributed to “problems with continuity”, that is, the assumption that the semantic functions should be continuous supposedly plays a role in the difficulties of giving a fully abstract fixpoint semantics. We show that for a large class of non-deterministic programming languages there is no fully abstract least fixpoint semantics even if one considers arbitrary functions (not necessarily continuous) over arbitrary partial orders (not necessarily complete).     

A survey on socio-semantic information retrieval

The rise of the Social Web and advances in the Semantic Web provides unprecedented possibilities for the development of novel methods to enhance the information retrieval (IR) process by including varying degrees of semantics. We shed light on the corresponding notion of semantically-enhanced information retrieval by presenting state-of-the art techniques in related research areas. We describe techniques based on the main processes of a typical IR workflow and map them onto three main types of semantics, which vary from formal semantic knowledge representations and content-based semantics to social semantics emerging through usage and user interactions.     

基于图像语义模型识别的道路汽车跟踪

在道路汽车跟踪算法研究中,论文提出了基于场景和运动主体模型的目标跟踪法,通过提取道路与汽车的高层信息属性,建立基于主体运行知识结构与操作方法的语义模型,实施对汽车的运动跟踪。这种目标跟踪算法体现了主体运行意图和操作的知识表达,丰富了目标跟踪算法的研究。