多媒体推理的概念框架

Up to now, AI technology is dominated by the Physical Symbolic System(PSS), in which symbolic information is used as the medium for reasoning, In these approaches, information other than symbols, such as image, graphics, and even video should first be represented by symbols, and after reasoning, the symbolic result is again changed into its original media form. In this paper, we will propose a new form of reasoning method called multimedia reasoning (MR), a kind of reasoning that is based on the different media such as text, image, video, audio and so on. By introducing the concept of multimedia transformation theory (MTT), it presents a conceptual framework for multimedia reasoning, In the end, it discusses the importance and potentials in applications.     

A general scheme for formalizing defaults using the predicateab(I, S)

In common sense reasoning two typical types of defaults are encountered.One is of the form “all birds can fly excepts b1,b2,…,and bm(m≥1)”,and the other “All birds can fly,but there exist exceptions”.The type of defaults is readily formalized but the other,as some researchers have noticad,is difficult to deal with.This paper establishes a general scheme for formalizing defaults of the two types,the key to which is the introduction of a two-argument predicate ab(I,S) to represent exceptional objects.     

Asymptotic stability of port‑hamiltonian systems with constant inputs

In this paper, the asymptotic stability of Port-Hamiltonian (PH) systems with constant inputs is studied. Constant inputs are useful for stabilizing systems at their nonzero equilibria and can be realized by step signals. To achieve this goal, two methods based on integral action and comparison principle are presented in this paper. These methods change the convex Hamiltonian function and the restricted damping matrix of the previous results into a Hamiltonian function with a local minimum and a positive semidefinite matrix, respectively. Due to common conditions of Hamiltonian function and damping matrix, the proposed method asymptotically stabilizes more classes of PH systems with constant inputs than the existing methods. Finally, the validity and advantages of the presented methods are shown in an example.     

Domain-specific ontology of botany

Domain-specific ontologies are greatly useful in knowledge acquisition, sharing and analysis. In this paper, botany-specific ontology for acquiring and analyzing botanical knowledge is presented. The ontology is represented in a set of well-defined categories, and each concept is viewed as an instance of certain category. The authors also introduce botany-specific axioms, an integral part of the ontology, for checking and reasoning with the acquired knowledge. Consistency, completeness and redundancy of the axioms are discussed.     

Formalizing Default Reasoning

Fuzzy set systems can be used to solve the problem with uncertain knowledge,and default logic can be used to solve the problem with incomplete knowledge,in some sense.In this paper,based on interval-valued fuzzy sets we introduce a method of inference which combines approximate reasoning an default ogic,and give the procedure of transforming monotonic reasoning into default reasoning.     

A new approximation algorithm for sorting of signed permutations

Sequence comparison leads to a combinatorial optimization problem of sorting permutations by reversals and transpositions.Namely,given any two permutations,find the shortest distance between them.This problem is related with genome rearrangement,genes are oriented in DNA sequences.The transpositions which have been studied in the liteature can be viewed as operations working on two consecutive segments of the genome.In this paper,a new kind of transposition which can work on two arbitrary segments of the genome is proposed,and the sorting of signed permutations by reversals and this new kind of transpostitions are studied.After establishing a lower bound on the number of operations needed,a 2-approximation algorithm is presented for this problem and an example is given to show that the performance ratio of the algorithm cannot be improved.     

Isomorphic transformations of uncertainties for incorporating EMYCIN-style and PROSPECTOR-style systems into a distributed expert system

In the past,expert systems exploited mainly the EMYCIN model and the PROSPECTOR mdoel to deal with uncertaintes.In other words,a lot of stand-alone expert systems which use thse two models are available.If we can use the Internet to Couple them together,their performance will be improved through cooperation.This is because the problem-solving ability of expert systems is greatly improved by the way of cooperation among different expert systems in a distributed expert system.Cooperation between different expert systems with these two heterogeneous uncertain reasoning models is essentially based on the transformations of uncertainties of propositions between these two models.In this paper,we discovered the exactly isomorphic transformations uncertaintis between uncertain reasoning models,as used by EMYCIN and PROSPECTOR.     

The completeness and applications of the formal system B

Since the formal deductive system (?) was built up in 1997, it has played important roles in the theoretical and applied research of fuzzy logic and fuzzy reasoning. But, up to now, the completeness problem of the system (?) is still an open problem. In this paper, the properties and structure of R0 algebras are further studied, and it is shown that every tautology on the R0 interval [0,1] is also a tautology on any R0 algebra. Furthermore, based on the particular structure of (?) -Lindenbaum algebra, the completeness and strong completeness of the system (?) are proved. Some applications of the system (?) in fuzzy reasoning are also discussed, and the obtained results and examples show that the system (?) is suprior to some other important fuzzy logic systems.     

基于空间推理的设计方法及其应用

In this paper,we discuss two main techniques concerning spatial reasoning in the designfield:representation of spatial relation and method of spatial reasoning. Based on this,we present aspatial reasoning model. Finally,we discuss an automatic advertising creation system which acts asan example of this model     

Reverse triple Ⅰ method of fuzzy reasoning

A theory of reverse triple I method with sustention degree is presented by using the implication operator R0 in every step of the fuzzy reasoning. Its computation formulas of supremum for fuzzy modus ponens and infimum for fuzzy modus tollens are given respectively. Moreover, through the generalization of this problem, the corresponding formulas of α-reverse triple I method with sustention degree are also obtained. In addition, the theory of reverse triple I method with restriction degree is proposed as well by using the operator R0, and the computation formulas of infimum for fuzzy modus ponens and supremum for fuzzy modus tollens are shown.     

时空推理研究进展

与时态和空间有关的推理问题是人工智能研究中重要的组成部分,在地理信息系统、时空数据库、CAD/CAM等领域有着重要应用.从本体、表示模型和推理方法3个方面分别介绍了时态推理和空间推理的发展,并在此基础上综述了时空结合推理的研究进展.讨论了目前时空推理领域存在的问题,并指出了今后的发展方向.     

Reasoning situated in time I: basic concepts*

Abstract

The needs of a real-time reasoner situated in an environment may make it appropriate to view error-correction and non-monotonicity as much the same thing. This has led us to formulate situated (or step) logic, an approach to reasoning in which the formalism has a kind of real-time self-reference that affects the course of deduction itself. Here we seek to motivate this as a useful vehicle for exploring certain issues in commonsense reasoning. In particular, a chief drawback of more traditional logics is avoided: from a contradiction we do not have all wffs swamping the (growing) conclusion set. Rather, we seek potentially inconsistent, but nevertheless useful, logics where the real-time self-referential feature allows a direct contradiction to be spotted and corrective action taken, as part of the same system of reasoning. Some specific inference mechanisms for real-time default reasoning are suggested, notably a form of introspection relevant to default reasoning. Special treatment of ‘now’ and of contradictions are the main technical devices here. We illustrate this with a computer-implemented real time solution to R. Moore's Brother Problem.     

A logical approach to representing and reasoning about space

The need for a formal language in which to express and reason about spatial concepts is of crucial importance in many areas of AI and visual systems. For the last five years, spatial reasoning research by the Qualitative Spatial Reasoning Group, University of Leeds, has centred on the development and application of such a language — the RCC spatial logic. Below, we briefly describe the work of the group in this area.     

自动推理技术发展的回顾与展望

介绍了国内外自动推理技术研究的历史,给出了自动推理的分类方法,阐述了各种自动推理技术的逻辑基础和基本思想,对各种推理模型的优缺点进行了系统的比较,并探讨了自动推理技术的发展趋势。     

Modality and interrupts

We suggest that modal operators, in addition to their well-understood semantic role in declarative systems, also mark points at which these systems can be interrupted. We use this idea to describe an interruptible declarative system that gradually refines its responses to queries. Although initial responses may be in error, a correct answer will be provided if arbitrarily large computational resources are available. The ideas presented generalize existing work on stratification of logic programs and the treatment of floundered subgoals.     

Multi-modal diagnosis combining case-based and model-based reasoning: a formal and experimental analysis

Integrating different reasoning modes in the construction of an intelligent system is one of the most interesting and challenging aspects of modern AI. Exploiting the complementarity and the synergy of different approaches is one of the main motivations that led several researchers to investigate the possibilities of building multi-modal reasoning systems, where different reasoning modalities and different knowledge representation formalisms are integrated and combined. Case-Based Reasoning (CBR) is often considered a fundamental modality in several multi-modal reasoning systems; CBR integration has been shown very useful and practical in several domains and tasks. The right way of devising a CBR integration is however very complex and a principled way of combining different modalities is needed to gain the maximum effectiveness and efficiency for a particular task. In this paper we present results (both theoretical and experimental) concerning architectures integrating CBR and Model-Based Reasoning (MBR) in the context of diagnostic problem solving. We first show that both the MBR and CBR approaches to diagnosis may suffer from computational intractability, and therefore a careful combination of the two approaches may be useful to reduce the computational cost in the average case. The most important contribution of the paper is the analysis of the different facets that may influence the entire performance of a multi-modal reasoning system, namely computational complexity, system competence in problem solving and the quality of the sets of produced solutions. We show that an opportunistic and flexible architecture able to estimate the right cooperation among modalities can exhibit a satisfactory behavior with respect to every performance aspect. An analysis of different ways of integrating CBR is performed both at the experimental and at the analytical level. On the analytical side, a cost model and a competence model able to analyze a multi-modal architecture through the analysis of its individual components are introduced and discussed. On the experimental side, a very detailed set of experiments has been carried out, showing that a flexible and opportunistic integration can provide significant advantages in the use of a multi-modal architecture.     

定性空间推理的分层递阶框架

定性空间推理是定性推理和空间推理的重要组成部分 .拓扑和形状是定性空间推理研究的关键问题 .针对定性空间推理已有一般框架存在的问题 ,提出了定性空间推理的分层递阶框架 ,并结合拓扑和形状方面的定性空间推理研究工作阐述了所提出的框架的有效性和合理性 .最后总结了分层递阶框架的要点并提出了基于该框架的进一步研究工作 .     

A hybrid system applied to epidemic screening

Although many knowledge-based systems (KBSs) focus on single-paradigm approaches to encoding knowledge (such as production rules), human experts rarely use a single type of knowledge to solve a real-world problem. A human expert usually combines a number of reasoning mechanisms. In recent years, rule-based reasoning (RBR), case-based reasoning (CBR) and model-based reasoning (MBR) have emerged as important and complementary reasoning methodologies in the intelligent systems area. For complex problem solving, it is useful to integrate RBR, CBR and MBR. In this paper, a hybrid epidemic screening KBS which integrates a deductive RBR system, an inductive CBR system and a quantitative MBR system is proposed. The system has been tested using real epidemic screening variables and data.     

YARM:基于MapReduce的高效可扩展的语义推理引擎

随着语义网的快速发展,RDF语义数据大量涌现.大规模RDF语义数据推理的一个主要问题是计算量大、完成计算需要消耗很长的时间.显然,传统的单机语义推理引擎难以处理大规模的语义数据.另一方面,现有的基于MapReduce的大规模语义推理引擎,缺乏对算法在分布和并行计算环境下执行效率的优化,使得推理时间仍然较长.此外,现有的推理引擎大多存在可扩展性方面的不足,难以适应大规模语义数据的增长需求.针对现有的语义推理系统在执行效率和可扩展性方面的不足,文中提出了一种基于MapReduce的并行化语义推理算法和引擎YARM.为了实现分布和并行计算环境下的高效推理,YARM做出了以下4点优化:(1)采用合理的数据划分模型和并行化算法,降低计算节点间的通信开销;(2)优化推理规则的执行次序,提升了推理计算速度;(3)设计了简洁的去重策略,避免新增作业处理重复数据;(4)设计实现了一种新的基于MapReduce的并行化推理算法.实验结果表明,在真实数据集和大规模合成数据集上,YARM的执行速度比当前最新的基于MapReduce的推理引擎快10倍左右,同时YARM还表现出更好的数据和系统可扩展性.     

The IKBALS project: Multi-modal reasoning in legal knowledge based systems

In attempting to build intelligent litigation support tools, we have moved beyond first generation, production rule legal expert systems. Our work integrates rule based and case based reasoning with intelligent information retrieval.When using the case based reasoning methodology, or in our case the specialisation of case based retrieval, we need to be aware of how to retrieve relevant experience. Our research, in the legal domain, specifies an approach to the retrieval problem which relies heavily on an extended object oriented/rule based system architecture that is supplemented with causal background information. We use a distributed agent architecture to help support the reasoning process of lawyers.Our approach to integrating rule based reasoning, case based reasoning and case based retrieval is contrasted to the CABARET and PROLEXS architectures which rely on a centralised blackboard architecture. We discuss in detail how our various cooperating agents interact, and provide examples of the system at work. The IKBALS system uses a specialised induction algorithm to induce rules from cases. These rules are then used as indices during the case based retrieval process.Because we aim to build legal support tools which can be modified to suit various domains rather than single purpose legal expert systems, we focus on principles behind developing legal knowledge based systems. The original domain chosen was theAccident Compensation Act 1989 (Victoria, Australia), which relates to the provision of benefits for employees injured at work. For various reasons, which are indicated in the paper, we changed our domain to that ofCredit Act 1984 (Victoria, Australia). This Act regulates the provision of loans by financial institutions.The rule based part of our system which provides advice on the Credit Act has been commercially developed in conjunction with a legal firm. We indicate how this work has lead to the development of a methodology for constructing rule based legal knowledge based systems. We explain the process of integrating this existing commercial rule based system with the case base reasoning and retrieval architecture.