基于认知反映的信念逻辑

Quine[9]提出了一类有关信念模态的难题,比如Cicero难题,这些难题的解读对模态逻辑语义具有重要的意义.目前的一阶模态逻辑普遍给予Quine难题以de re/de dicto解读.本文指出de re/de dicto解读存在缺陷,并且认为为了解读Quine难题,需要在一阶模态逻辑的模型中引入一个认知反映关系.在此观念下,本文提出了一个新的一阶模态逻辑系统--基于认知反映的信念逻辑.     

面向行动的信念更新

基于可能模型方法 ( possible m odel approach,简称 PMA) ,提出了面向行动的信念更新的概念 ,证明了在信息完备的情境演算系统中 ,一个一阶公式在情境 s下成立当且仅当它属于情境 s下的信念集 .这一结果为有效避免情境演算推理中二阶归纳公理的使用提供了一条可行的途径 ,也为基于意向驱动的 agent模型的建立以及面向 agent的程序设计语言 AOPL ID( agent-oriented programm ing language with intention driver)的提出提供了必要的理论基础.     

The systematic design of visual languages applied to logical reasoning

Visual languages are distinguished by a number of graphical objects and their relations, usually arranged in the two-dimensional plane. While objects and relations are syntactical containers which are used to represent some information, the question arises how to systematically treat all possible syntactical containers given the richness and complexity of the underlying geometry. This paper adopts the intersection paradigm applied in the context of spatial reasoning, which ensures the systematic identification of all conceivable well-formed diagrams. This allows the exhaustive analysis of a visual language. As an example, it is shown how this method enables a thorough understanding of the relations of the graphical elements of linear diagrams which represent monadic first-order logic. The consideration of indeterminate sets even demonstrates the effectiveness of this approach for a representation that includes a total of 512 relations.     

利用谓词/变迁网证明的一阶谓词逻辑命题

研究了证明一般的一阶谓词逻辑命题的方法,根据网逻辑的思想,利用谓词/变迁网对一般形式的一阶谓词逻辑命题进行了图形表示,提出了2种一阶谓词逻辑命题的证明方法：图形证明法和矩阵证明法。举出一个实际的例子来说明证明思路。     

Representing model theory in a type-theoretical logical framework

In a broad sense, logic is the field of formal languages for knowledge and truth that have a formal semantics. It tends to be difficult to give a narrower definition because very different kinds of logics exist. One of the most fundamental contrasts is between the different methods of assigning semantics. Here two classes can be distinguished: model theoretical semantics based on a foundation of mathematics such as set theory, and proof theoretical semantics based on an inference system possibly formulated within a type theory.Logical frameworks have been developed to cope with the variety of available logics unifying the underlying ontological notions and providing a meta-theory to reason abstractly about logics. While these have been very successful, they have so far focused on either model or proof theoretical semantics. We contribute to a unified framework by showing how the type/proof theoretical Edinburgh Logical Framework (LF) can be applied to the representation of model theoretical logics.We give a comprehensive formal representation of first-order logic, covering both its proof and its model theoretical semantics as well as its soundness in LF. For the model theory, we have to represent the mathematical foundation itself in LF, and we provide two solutions for that. Firstly, we give a meta-language that is strong enough to represent the model theory while being simple enough to be treated as a fragment of untyped set theory. Secondly, we represent Zermelo-Fraenkel set theory and show how it subsumes our meta-language. Specific models are represented as LF morphisms.All representations are given in and mechanically verified by the Twelf implementation of LF. Moreover, we use the Twelf module system to treat all connectives and quantifiers independently. Thus, individual connectives are available for reuse when representing other logics, and we obtain the first version of a feature library from which logics can be pieced together.Our results and methods are not restricted to first-order logic and scale to a wide variety of logical systems, thus demonstrating the feasibility of comprehensively formalizing large scale representation theorems in a logical framework.     

基于目标演绎距离的一阶逻辑子句集预处理方法

一阶逻辑定理证明是人工智能的核心基础,研究一阶逻辑自动定理证明器的相关理论和高效的算法实现具有重要的学术意义。当前一阶逻辑自动定理证明器首先通过子句集预处理约简子句集规模,然后通过演绎方法对定理进行判定。现有的应用于证明器中的子句集预处理方法普遍只从与目标子句项符号相关性角度出发,不能很好地从文字的互补对关系中体现子句间的演绎。为了在子句集预处理时从演绎的角度刻画子句间的关系,定义了目标演绎距离的概念并给出了计算方法,提出了一种基于目标演绎距离的一阶逻辑子句集预处理方法。首先对原始子句集进行包含冗余子句约简并应用纯文字删除规则,然后根据目标子句计算剩余子句集中的文字目标演绎距离、子句目标演绎距离,并最终通过设定子句演绎距离阈值来实现对子句集的进一步预处理。将该预处理方法应用于顶尖证明器Vampire,以2017年国际一阶逻辑自动定理证明器标准一阶逻辑问题组竞赛例为测试对象,在标准的300 s内,加入提出的子句集预处理方法的Vampire4.1相比原始的Vampire4.1多证明4个定理,能证明10个Vampire4.1未证明的定理,占其未证明定理总数的13.5%;在证明的定理中,提出的...     

运动补偿时域滤波中基于残差图像滤波的更新策略

现有的比较成熟的可伸缩编码框架是基于运动补偿时域滤波技术的。改进了运动补偿时域滤波中的更新操作，并引入去块滤波。更新操作过程中，要求更新块中的像素所对应的预测运动向量完全一致，否则不参与更新操作。更新操作前，对残差图像在边缘级和采样点级进行滤波控制。通过对高通信号的去块滤波，减少更新块中的伪边界成分，同时减轻块效应对后继预测操作的影响，改善编码效率。实验结果表明该方法能够改进图像的主观质量，提高低运动量的图像序列的编码性能。     

一阶谓词逻辑的图形推理法

针对已有一阶谓词逻辑推理方法中存在的推理效率低等问题,研究一种基于谓词/变迁系统的图形推理法。定义了描述谓词间与/或关系的谓词-与/或图,借助谓词-与/或图表示谓词/变迁系统,提出一种实现反向推理的目标制导的图形推理法。该方法推理效率高,较已有的推理方法具有一定的优越性。     

一阶逻辑在关系数据库中的应用

一阶逻辑能唯一地作为关系数据库的统一语言，对关系数据库的可用性很多，本文主要讨论一些利用Prolog语言实现的应用。     

Iterated belief change in the situation calculus

John McCarthy's situation calculus has left an enduring mark on artificial intelligence research. This simple yet elegant formalism for modelling and reasoning about dynamic systems is still in common use more than forty years since it was first proposed. The ability to reason about action and change has long been considered a necessary component for any intelligent system. The situation calculus and its numerous extensions as well as the many competing proposals that it has inspired deal with this problem to some extent. In this paper, we offer a new approach to belief change associated with performing actions that addresses some of the shortcomings of these approaches. In particular, our approach is based on a well-developed theory of action in the situation calculus extended to deal with belief. Moreover, by augmenting this approach with a notion of plausibility over situations, our account handles nested belief, belief introspection, mistaken belief, and handles belief revision and belief update together with iterated belief change.     

基于状态包过滤的防火墙技术

本文首先介绍了防火墙的基本技术——包过滤的工作原理。通过一个防火墙构建实例，显示了传统包过滤的局限性，进而引人状态包过滤的概念，最后对其工作原理和实现的关键部分进行分析。     

A model-based belief revision system

Numerous belief revision and update semantics have been proposed in the literature in the past few years, but until recently, no work in the belief revision literature has focussed on the problem of implementing these semantics, and little attention has been paid to algorithmic questions. In this paper, we present and analyze our update algorithms built in Immortal, a model-based belief revision system. These algorithms can work for a variety of model-based belief revision semantics proposed to date. We also extend previously proposed semantics to handle updates involving the equality predicate and function symbols and incorporate these extensions in our algorithms. As an example, we discuss the use of belief revision semantics to model the action-augmented envisioning problem in qualitative simulation, and we show the experimental results of running an example simulation in Immortal.     

Controlled-topology filtering

Many applications require the extraction of isolines and isosurfaces from scalar functions defined on regular grids. These scalar functions may have many different origins: from MRI and CT scan data to terrain data or results of a simulation. As a result of noise and other artifacts, curves and surfaces obtained by standard extraction algorithms often suffer from topological irregularities and geometric noise.While it is possible to remove topological and geometric noise as a post-processing step, in the case when a large number of isolines are of interest there is a considerable advantage in filtering the scalar function directly. While most smoothing filters result in gradual simplification of the topological structure of contours, new topological features typically emerge and disappear during the smoothing process.In this paper, we describe an algorithm for filtering functions defined on regular 2D grids with controlled topology changes, which ensures that the topological structure of the set of contour lines of the function is progressively simplified.     

Unification of nonlinear filtering in the context of binary logical calculus,part I: Binary filters

The mathematical structure of nonlinear filtering is expressed in the context of binary logic. This first part of a two-part study concerns the binary setting. Operator properties, such as antiextensivity and idempotence, are expressed in finite logical expressions, as are the Matheron representation for morphological filters and its extension to translation-invariant operators, thereby giving simplicity to both operational properties and representations and also exposing the manner in which logic methods can be used for filter design and analysis. The second part of the study treats gray-scale filters.     

Toward knowledge-rich data mining

This position paper proposes knowledge-rich data mining as a focus of research, and describes initial steps in pursuing it.     

流体随机Petri网的一阶混杂Petri网模型

为了借用一阶混杂Petri网(First-Order Hybrid Petri Nets)的建模原语和分析方法来分析流体随机Petri网(Fluid Stochastic Petri Nets)以克服流体随机Petri网数值分析方法的局限性,本文提出了一种流体随机Petri网转换成一阶混杂Petri网的形式化描述方法,并对其转换的正确性进行了证明,最后通过实例分析了流体随机Petri网转换成一阶混杂Petri网的必要性.