支持规则推理的神经网络模型

本文研究了支持规则推理的神经网络模型，表明通常执行的推理与符号系统在方法上确实相似，只是它们对常识推理提供了更多的方法。CONSYDERR是一种支持常识推理的连接结构，其目的是给出常识推理的一种模型，并纠正传统规则系统中的脆弱性问题。本项工作表明，推理的连接模型不仅实现了符号推理，而且是一种更好的常识推理的计算模型。     

关于常识推理的统计途径

一、引言常识推理是人工智能的一个主要研究领域,在人类间题求解中是不可缺少的,但目前还没有关于它的严格定义,它泛指人们在日常生活中的推理。一般地说,常识推理具有下     

常识问题——常识推理的逻辑基础

本文主要讨论常识推理的逻辑基础，基于一条从非单调推理到常识推理的技术途径，由此指出在更一般意义上形式化常识推是的一些结果，它建立常识逻辑和解决常识问题提供了有用的基础工具。     

老年人看护系统中常识推理的研究

根据老年人看护的需求,将常识推理运用到智能家庭老年人看护推理系统中,并将其与领域本体相结合,对系统实现的主要技术,即基于本体的常识表示与存储、规则的表示以及常识的推理进行探讨和构想,并通过典型应用实例验证了常识推理在老年人看护系统中的可行性、有效性及其重要性。     

前言

国家高技术计划智能机主题已把“常识推理”定为该计划第二阶段基础研究的三个主攻方向之一。九二年六月专家组在汕头大学召开了第一次“关于常识推理”的学术研讨会。参加这次研讨会的共有十八位活跃在我国人工智能基础研究第一线的中青年学者。摆在读者面前的这期专集是从会上报告的论文中选出的较好的十篇。     

可废除推理研究

非单调推理是针对常识推理而提出的,但是标准非单调逻辑都存在可计算性问题,如何提出一种     

非单调性和不一致性的处理——一个基于线性逻辑的方法

本文提出一种基于线性逻辑的理论L1,它除了能较好地反映常识推理的非单调性外,还可以在矛盾存在的情况下继续组织有效的推理。     

面向对象逻辑语言SCKE中的限制推理

限制理论是形式化常识知识并进行常识推理的一种重要方法．本文主要研究将限制理论转化为面向对象逻辑语言的可能性，并实现了完成这个转换的编译器．按面向对象逻辑语言的语义运行编译后的程序，可得到与原限制理论相同的结果．将该编译器嵌入面向对象逻辑语言解释器中，可以大大提高该语言的表达能力，特别是可以实现对常识知识表示和常识推理的支持．     

逻辑程序中的否定问题与非单调逻辑

1引言 常识推理的一个共同特性是在不完全知识下的推理,非单调推理提供了不完全知下的推理方法,它能在有限如识的基础上得出一些结论,而当知识进一步丰富时这些结论是可销的。最著名的非单     

容错推理系统FTRS的设计

常识揄的难点是前提知识的不完备性、揄规则的不精确性以及知识中显性或隐性矛盾存在的普遍性。常识推理的第一个特点是“常识性”,“常识     

On nonmonotonic reasoning with the method of sweeping presumptions

Reasoning almost always occurs in the face of incomplete information. Such reasoning is nonmonotonic in the sense that conclusions drawn may later be withdrawn when additional information is obtained. There is an active literature on the problem of modeling such nonmonotonic reasoning, yet no category of method-let alone a single method-has been broadly accepted as the right approach. This paper introduces a new method, called sweeping presumptions, for modeling nonmonotonic reasoning. The main goal of the paper is to provide an example-driven, nontechnical introduction to the method of sweeping presumptions, and thereby to make it plausible that sweeping presumptions can usefully be applied to the problems of nonmonotonic reasoning. The paper discusses a representative sample of examples that have appeared in the literature on nonmonotonic reasoning, and discusses them from the point of view of sweeping presumptions.     

Default reasoning and belief revision: A syntax-independent approach

As an important variant of Reiter‘s default logic.Poole(1988) developed a nonmonotonic reasoning framework in the classical first-order language,Brewka and Nebel extended Poole‘s approach in order to enable a representation of priorities between defaults.In this paper a general framework for default reasoning is presented,which can be viewed as a generalization of the three approaches above.It is proved that the syntax-independent default reasoning in this framework is identical to the general belief revision operation introduced by Zhang et al.(1997).This esult provides a solution to the problem whether there is a correspondence between belief revision and default logic for the infinite case .As a by-product,an answer to the the question,raised by Mankinson and Gaerdenfors(1991),is also given about whether there is a counterpart contraciton in nonmonotonic logic.     

Strategies in Human Nonmonotonic Reasoning

Although humans seem adept at drawing nonmonotonic conclusions, the nonmonotonic reasoning systems that researchers develop are complex and do not function with such ease. This paper explores people's reasoning processes in nonmonotonic problems. To avoid the problem of people's conclusions being based on knowledge rather than on some reasoning process, we developed a scenario about life on another planet. Problems were chosen to allow the systematic study of people's understanding of strict and nonstrict rules and their interactions. We found that people had great difficulty reasoning and we identified a number of negative factors influencing their reasoning. We also identified three positive factors which, if used consistently, would yield rational and coherent reasoning—but no subject achieved total consistency. (Another possible positive factor, specificity, was considered but we found no evidence for its use.) It is concluded that nonmonotonic reasoning is hard. When people need to reason in a domain where they have no preconceived ideas, the foundation for their reasoning is neither coherent nor rational. They do not use a nonmonotonic reasoning system that would work regardless of content. Thus, nonmonotonic reasoning systems that researchers develop are expected to do more reasoning than humans actually do!     

基于自动推理技术的智能规划方法

对几种智能规划方法中利用的逻辑演绎与推理技术予以分析,分别介绍利用命题逻辑的基于可满足性的规划方法与规划系统,利用模态逻辑与析取推理的Conformant规划方法与规划系统,利用非单调逻辑的规划方法和利用模糊描述逻辑的Flexible规划方法,并结合国际规划竞赛和相关论文等的实验结论说明上述方法的有效性和可行性.最后,提出目前基于自动推理技术的智能规划方法所面临的挑战、可能的处理方法以及与之相关的研究热点与趋势.     

An Interpretation of Default Logic in Minimal Temporal Epistemic Logic

When reasoning about complex domains, where information available is usually only partial, nonmonotonic reasoning can be an important tool. One of the formalisms introduced in this area is Reiter's Default Logic (1980). A characteristic of this formalism is that the applicability of default (inference) rules can only be verified in the future of the reasoning process. We describe an interpretation of default logic in temporal epistemic logic which makes this characteristic explicit. It is shown that this interpretation yields a semantics for default logic based on temporal epistemic models. A comparison between the various semantics for default logic will show the differences and similarities of these approaches and ours.     

Operational Concepts of Nonmonotonic Logics Part 2: Autoepistemic Logic

The subject of nonmonotonic reasoning is reasoning with incompleteinformation. One of the main approaches is autoepistemic logic inwhich reasoning is based on introspection. This paper aims at providing a smooth introduction to this logic,stressing its motivation and basic concepts. The meaning (semantics)of autoepistemic logic is given in terms of so-called expansionswhich are usually defined as solutions of a fixed-point equation. Thepresent paper shows a more understandable, operational method fordetermining expansions. By improving applicability of the basicconcepts to concrete examples, we hope to make a contribution to awider usage of autoepistemic logic in practical applications.     

基于标记逻辑的非单调推理（Ⅰ）

我们把标记逻辑定义在一个特殊双格上,通过比较标记选取结论,从而同时捕捉超协调（容错）推理和非单调推理．本文介绍标记逻辑程序的句法与语义构造,提出诱导序列及其极限的概念,给出极限存在的等价条件,并证明一个重要结果：诱导序列基本定理,它是后续讨论的基础．     

Autoepistemic logic of first order and its expressive power

We study the expressive power of first-order autoepistemic logic. We argue that full introspection of rational agents should be carried out by minimizing positive introspection and maximizing negative introspection. Based on full introspection, we propose the maximal well-founded semantics that characterizes autoepistemic reasoning processes of rational agents, and show that breadth of the semantics covers all theories in autoepistemic logic of first order, Moore's AE logic, and Reiter's default logic. Our study demonstrates that the autoepistemic logic of first order is a very powerful framework for nonmonotonic reasoning, logic programming, deductive databases, and knowledge representation.This research is partially supported by NSERC grant OGP42193.     

The Nature of Nonmonotonic Reasoning

Conclusions reached using common sense reasoning from a set of premises are often subsequently revised when additional premises are added. Because we do not always accept previous conclusions in light of subsequent information, common sense reasoning is said to be nonmonotonic. But in the standard formal systems usually studied by logicians, if a conclusion follows from a set of premises, that same conclusion still follows no matter how the premise set is augmented; that is, the consequence relations of standard logics are monotonic. Much recent research in AI has been devoted to the attempt to develop nonmonotonic logics. After some motivational material, we give four formal proofs that there can be no nonmonotonic consequence relation that is characterized by universal constraints on rational belief structures. In other words, a nonmonotonic consequence relation that corresponds to universal principles of rational belief is impossible. We show that the nonmonotonicity of common sense reasoning is a function of the way we use logic, not a function of the logic we use. We give several examples of how nonmonotonic reasoning systems may be based on monotonic logics.     

Minimal Belief and Negation as Failure in Multi-Agent Systems

We propose an epistemic, nonmonotonic approach to the formalization of knowledge in a multi-agent setting. From the technical viewpoint, a family of nonmonotonic logics, based on Lifschitz's modal logic of minimal belief and negation as failure, is proposed, which allows for formalizing an agent which is able to reason about both its own knowledge and other agents' knowledge and ignorance. We define a reasoning method for such a logic and characterize the computational complexity of the major reasoning tasks in this formalism. From the practical perspective, we argue that our logical framework is well-suited for representing situations in which an agent cooperates in a team, and each agent is able to communicate his knowledge to other agents in the team. In such a case, in many situations the agent needs nonmonotonic abilities, in order to reason about such a situation based on his own knowledge and the other agents' knowledge and ignorance. Finally, we show the effectiveness of our framework in the robotic soccer application domain.