A Qualitative Approach to Syllogistic Reasoning

In this paper we present a new approach to a symbolic treatment of quantified statements having the following form Q A's are B's, knowing that A and B are labels denoting sets, and Q is a linguistic quantifier interpreted as a proportion evaluated in a qualitative way. Our model can be viewed as a symbolic generalization of statistical conditional probability notions as well as a symbolic generalization of the classical probabilistic operators. Our approach is founded on a symbolic finite M-valued logic in which the graduation scale of M symbolic quantifiers is translated in terms of truth degrees. Moreover, we propose symbolic inference rules allowing us to manage quantified statements.     

电路宽度制导的布尔推理

在基于逻辑电路的布尔推理过程中,经常用到二又判决图(BDD)与布尔可满足性(SAT)相结合的算法．由于电路宽度能很好地反映电路的复杂性,提出了一种基于电路宽度的启发式策略,根据电路宽度来实现SAT算法与BDD算法的交替．充分发挥两者的优势,不仅可以防止因构造BDD可能导致的内存爆炸,而且还能避免SAT算法可能遇到的超时现象．与以往同类策略相比,该启发式策略更节省计算资源,提高算法性能．针对组合电路的测试产生实验,证实了其在布尔推理中的效率．     

Relational Program Reasoning Using Compiler IR

Relational program reasoning is concerned with formally comparing pairs of executions of programs. Prominent examples of relational reasoning are program equivalence checking (which considers executions from different programs) and detecting illicit information flow (which considers two executions of the same program). The abstract logical foundations of relational reasoning are, by now, sufficiently well understood. In this paper, we address some of the challenges that remain to make the reasoning practicable. Two major ones are dealing with the feature richness of programming languages such as C and with the weakly structured control flow that many real-world programs exhibit. A popular approach to control this complexity is to define the analyses on the level of an intermediate program representation (IR) such as one generated by modern compilers. In this paper we describe the ideas and insights behind IR-based relational verification. We present a program equivalence checker for C programs that operates on LLVM IR. To extend the reach of the approach and to make it more efficient, we show how dynamic analyses can be employed to support and strengthen the static verification. The effectiveness of the approach is demonstrated by automatically verifying equivalence of functions from different implementations of the standard C library.     

基于布尔推理的极大相容块构造方法

极大相容块是非完备信息系统中的最小知识单元,在非完备信息系统的知识表示、属性约简、粒度分析及知识获取方面有重要的应用价值。提出了一种获取非完备信息系统中极大相容块的方法。通过定义的区分关系,构造了新的布尔函数,证明了极大相容块与构造的布尔公式的素蕴含之间存在一一对应的关系。因此,这种新的布尔函数可以被用来获得系统的所有极大相容块,这将有助于非完备信息系统中的知识获取。     

Relational Case-based Reasoning for Carcinogenic Activity Prediction

Lazy learning methods are based on retrieving a set of precedent cases similar to a new case. An important issue of these methods is how to estimate the similarity among a new case and the precedents. Usually, similarity measures require that cases have a prepositional representation. In this paper we present Shaud, a similarity measure useful to estimate the similarity among relational cases represented using featureterms. We also present results of the application of Shaud forsolving classification tasks. Specifically we used Shaud for assessingthe carcinogenic activity of chemical compounds in the Toxicology dataset.     

Reasoning Boolean operation based modeling for heterogeneous objects

A reasoning Boolean operation based CAD modeling approach applied to construct heterogeneous material objects is presented. This reasoning Boolean operation consists of a merging operation and an extracting operation, and it is executed according to the material-dominant information defined in the designed heterogeneous object database. In addition to the material-dominant Boolean union, subtraction, and intersection, a new Boolean complex_union operation is defined and introduced to the set of the reasoning Boolean operation. The Boolean complex_union ‘assembles’ the results of the material-dominant Boolean intersection and subtraction to form a new modeling assembly for the heterogeneous object. Due to the CAD-based nature, the thus formed heterogeneous model can be readily implemented with advanced CAD/CAE/CAM software for integrated design, analysis, and simulation. An example of such an application, its hierarchy of the model database, and the major steps of the model construction are described.     

An Extended Relational Data Model For Probabilistic Reasoning

Probabilistic methods provide a formalism for reasoning aboutpartial beliefs under conditions of uncertainty. This paper suggests a newrepresentation of probabilistic knowledge. This representation encompassesthe traditional relational database model. In particular, it is shown thatprobabilistic conditional independence is equivalent to the notion of generalized multivalued dependency. More importantly,a Markov network can be viewed as a generalized acyclic joindependency. This linkage between these two apparently different butclosely related knowledge representations provides a foundation fordeveloping a unified model for probabilistic reasoning and relationaldatabase systems.     

提高一阶多值逻辑Tableau推理效率的布尔剪枝方法

含有量词的一阶多值Tableau方法具有统一的扩展规则,并由Zabel等人给出了可靠性和完备性的证明,但由于扩展后的分枝随着真值数目的增加而呈指数的增加,因而影响了机器推理执行的效率,该文提出了布尔剪枝方法,将带符号的公式与集合的上集／下集联系起来,使含量词的一阶多值逻辑公式的扩展规则大大简化,进一步,通过对布尔剪枝方法的分析,建立了一类特殊一阶多值逻辑正则公式的更为简洁的Tableau推理方法,该方法使得含量词的一阶多值逻辑Tableau推理类同于经典逻辑Tableau方法。     

A Reasoning System of Ternary Projective Relations

This paper introduces a reasoning system based on a previously developed model for ternary projective relations between spatial objects. The model applies to spatial objects of the kind point and region is based on basic projective invariants and takes into account the size and shape of the three objects that are involved in a relation. The reasoning system proposes a set of permutation and composition rules, which allow the inference of unknown relations from given ones.     

System LS: A Three-Tiered Nonmonotonic Reasoning System

In this paper, a formal system of nonmonotonic reasoning is developed, which takes as its inspiration the manner in which some people make logically justifiable conclusions about nonmonotonic reasoning problems. The people, when asked about individuals, compare the logical strength of the arguments relating any sets to which the individual belongs, to other sets. A three-tiered system of rules including rules of System P as well as Transitivity and Monotonicity is developed. The system, known as System LS for logical strength, deals with three levels of non-strict relationships:

• α ₁β  α are normally β ( more than half of the α are β ) ;

       
  
  

Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching

One of the obstacles to widely using first-order logic languages is the fact that relational inference is intractable in the worst case. This paper presents an any-time relational inference algorithm: it proceeds by stochastically sampling the inference search space, after this space has been judiciously restricted using strongly-typed logic-like declarations.We present a relational learner producing programs geared to stochastic inference, named STILL, to enforce the potentialities of this framework. STILL handles examples described as definite or constrained clauses, and uses sampling-based heuristics again to achieve any-time learning.Controlling both the construction and the exploitation of logic programs yields robust relational reasoning, where deductive biases are compensated for by inductive biases, and vice versa.     

多Agent系统中JESS推理系统改进算法

JESS系统推理机的核心策略算法使用经典的RETE算法,以存储空间换取执行的时间,当推理的知识库比较大时,对存储空间的消耗是惊人的.这篇文章从多Agent出发,提出通过共享规则和事实等方法减少存储的消耗,并给出数学公式加以验证.     

全要素模型与关系模型的关系解析映射

为实现基于全要素模型的空间信息关系数据库存储,首先对全要素模型(FullFeatureModel,FFM)及其关系类型进行了分析,阐述了FFM与关系模型映射的内容;然后提出了一种FFM与关系模型的关系解析映射方法,给出了基于图论的具体映射过程与算法;最后实现了表达FFM的复杂图与关系模式之间的转换,并给出了具体实例;为空间信息基于关系数据库的集成与共享等奠定了基础。     

System R: A Relational Data Base Management System

A relational approach makes this experimental data base management system unusually easy to install and use. Some of the decisions made in System R design in order to enhance usability also offer major bonuses in other areas.     

A Relational Representation of an Abstract Type System

Programming languages have traditionally had more data types than database systems. The flexibility of abstract types could make a database system more useful in supporting application development. Abstract types allow users to think about and manipulate data in terms and structures that they are familiar with. This paper proposes that databases have a type system interface and describes a representation of a type system in terms of relations. The type system model supports a variety of programming language constructs, such as user-defined parameterized data types and user-defined generic operations. The efficiency of the type system is compared to the access time of the database system.     

决策支持系统相关技术综述

决策支持系统是现代化管理的重要手段,数据挖掘、数据仓库、在线分析又是它的三个主要技术,主要从特点、应用现状、涉及到的问题、技术基础等方面对其采用的三个技术作了详细介绍。     

A Meteorological Fuzzy Expert System Incorporating Subjective User Input

We present a fuzzy expert system, MEDEX, for forecasting gale-force winds in the Mediterranean basin. The most successful local wind forecasting in this region is achieved by an expert human forecaster with access to numerical weather prediction products. That forecaster's knowledge is expressed as a set of ‘rules-of-thumb’. Fuzzy set methodologies have proved well suited for encoding the forecaster's knowledge, and for accommodating the uncertainty inherent in the specification of rules, as well as in subjective and objective input. MEDEX uses fuzzy set theory in two ways: as a fuzzy rule base in the expert system, and for fuzzy pattern matching to select dominant wind circulation patterns as one input to the expert system. The system was developed, tuned, and verified over a two-year period, during which the weather conditions from 539 days were individually analyzed. Evaluations of MEDEX performance for both the onset and cessation of winter and summer winds are presented, and demonstrate that MEDEX has forecasting skill competitive with the US Navy's regional forecasting center in Rota, Spain. Received 5 May 1999 / Revised 8 August 2000 / Accepted in revised form 23 April 2001     

群体决策支持系统中一种偏好集结模型

针对目前常用决策理论的不足,在计算机群体决策支持系统（GDSS）的偏好agent中用一种模糊数N^-模拟决策者的心理偏好,采用相关参数表达决策者的性格特征等个性因素。从决策人的角度出发,提出了一种偏好集结模型,使群体综合偏好照顾到个性因素,为群体决策提供了一个新的思路。