bluuebunny/crossref_metadata_2025_split huggingface dataset:
Qualitative reasoning overtime: history and current prospects
Authors: Travé-Massuyès Louise 
Published: July 2009

AbstractThis paper provides a historical summary of the motivations which have led several research communities to contemplate qualitative techniques. Qualitative reasoning satisfies various problem solving needs in high level decision tasks, embodied in a set of tools which allow deep knowledge to be put in compatible form with software requirements while still remaining realistic. An overview of these mathematical formalisms is presented; qualitative simulation is introduced as one of the most significant outcomes. Finally, some current research issues concerning temporal aspects of qualitative reasoning are discussed.
From knowledge bases to decision models
Authors: Wellman Michael P. , Breese John S. , Goldman Robert P. 
Published: July 2009

AbstractIn recent years there has been a growing interest among AI researchers in probabilistic and decision modelling, spurred by significant advances in representation and computation with network modelling formalisms. In applying these techniques to decision support tasks, fixed network models have proven to be inadequately expressive when a broad range of situations must be handled. Hence many researchers have sought to combine the strengths of flexible knowledge representation languages with the normative status and well-understood computational properties of decision-modelling formalisms and algorithms. One approach is to encode general knowledge in an expressive language, then dynamically construct a decision model for each particular situation or problem instance. We have developed several systems adopting this approach, which illustrate a variety of interesting techniques and design issues.
The qualitative representation of physical systems
Authors: Coiera Enrico 
Published: July 2009

AbstractThe representation of physical systems using qualitative formalisms is examined in this review, with an emphasis on recent developments in the area. The push to develop reasoning systems incorporating deep knowledge originally focused on naive physical representations, but has now shifted to more formal ones based on qualitative mathematics. The qualitative differential constraint formalism used in systems like QSIM is examined, and current efforts to link this to competing representations like Qualitative Process Theory are noted. Inference and representation are intertwined, and the decision to represent notions like causality explicitly, or infer it from other properties, has shifted as the field has developed. The evolution of causal and functional representations is thus examined. Finally, a growing body of work that allows reasoning systems to utilize multiple representations of a system is identified. Dimensions along which multiple model hierarchies could be constructed are examined, including mode of behaviour, granularity, ontology, and representational depth.
Principles and practice in verifying rule-based systems
Authors: Preece Alun D. , Shinghal Rajjan , Batarekh Aïda 
Published: July 2009

AbstractThis paper surveys the verification of expert system knowledge bases by detecting anomalies. Such anomalies are highly indicative of errors in the knowledge base. The paper is in two parts. The first part describes four types of anomaly: redundancy, ambivalence, circularity, and deficiency. We consider rule bases which are based on first-order logic, and explain the anomalies in terms of the syntax and semantics of logic. The second part presents a review of five programs which have been built to detect various subsets of the anomalies. The four anomalies provide a framework for comparing the capabilities of the five tools, and we highlight the strengths and weaknesses of each approach. This paper therefore provides not only a set of underlying principles for performing knowledge base verification through anomaly detection, but also a survey of the state-of-the-art in building practical tools for carrying out such verification. The reader of this paper is expected to be familiar with first-order logic.
A unifying framework for concept-learning algorithms
Authors: de Raedt Luc , Bruynooghe Maurice 
Published: July 2009

AbstractA unifying framework for concept-learning, derived from Mitchell's Generalization as Search-paradigm, is presented. Central to the framework is the generic algorithm Gencol. Gencol forms a synthesis of existing concept-learning algorithms as it identifies the key issues in concept-learning: the representation of concepts and examples, the search strategy and heuristics, and the operators that transform one concept-description into another one when searching the concept description space. Gencol is relevant for practical purposes as it offers a solid basis for the design and implementation of concept-learning algorithms. The presented framework is quite general as seemingly disparate algorithms such as TDIDT, AQ, MIS and version spaces fit into Gencol.
Artificial intelligence in business II: Development, integration and organizational issues
Authors: O'Leary Daniel E. , Kingston John 
Published: July 2009

AbstractThe purpose of this paper is to review the use of knowledge-based systems and artificial intelligence (AI) in business. Part I of this paper provided a broad survey of the use of AI in business, summarizing the application of AI in a number of business domains. In addition, it also provided a summary of the use of different forms of knowledge representation in business applications. Part I has a large set of references, including a number of survey papers, focusing on AI in business. Part II of this paper consists of more detailed analysis of particular systems or issues affecting AI in business. It examines technical issues which are central to the construction of business AI systems, and it also examines the commercial contribution made by methods for the development of AI systems. In addition, part II looks at integration between AI and more traditional information systems. AI can be used to add value to many existing information systems, such as database management systems. Particular attention is given to the integration of AI with operations research, which is the one of the primary “competitors” of AI, providing an alternative set of support tools for decision making.Business organizations are not concerned only with technology issues; there is also concern about the impact of AI on organizations. Further, the evaluation of AI often is based on an economic view of the world. Part II therefore investigates the organizational impact of AI, and the economics of AI, including issues such as value creation. The format of Part II is as follows: Section 8 analyses techniques for improving the performance of AI systems, thus maximizing economic return. Section 9 looks at different forms of uncertainty and ambiguity which must be dealt with by AI systems. It examines the contributions of fuzzy logic and numerical measures of certainty to handling these problems. Section 10 examines the usefulness of different approaches to knowledge acquisition in business situations, and investigates the benefits of methodological approaches to AI applications. It also looks at more recent AI programming techniques which eliminate the need for knowledge elicitation from an expert: neural networks, case-based reasoning and genetic algorithms are discussed. Sections 11 and 12 examine issues of integrating AI systems. Generally, the use of AI in business settings must ultimately be integrated with the broader base of corporate information systems. Section 11 looks at integration with information systems in general, and section 12 looks particularly at integration with operations research. Sections 13 and 14 review the organizational and economic impact of AI. Finally, section 15 provides a brief summary of part II.
Fuzzy systems and fuzzy expert control: An overview
Authors: Tzafestas Spyros G. 
Published: July 2009

AbstractThis paper presents an overview of fuzzy set theory and its application to the analysis and design of fuzzy expert control systems. Starting with a short account of the basic concepts and properties of fuzzy sets and fuzzy reasoning, a few fuzzy rule-based controllers, viz, basic single-input singleoutput fuzzy control, self-organizing fuzzy control, fuzzy PID supervisor, and the fuzzy PID incremental controller, are described in some detail. Then a survey of the theoretical results and applications is provided which gives a good picture of the current status of the field. This survey includes the work on neuro-fuzzy systems, and software systems for the representation and processing of fuzzy information. The paper closes with four application examples which show the type of results that must be expected from fuzzy expert control.
Artificial intellugence and knowledge based systems in molecular biology
Authors: Fox John , Rawlings Christopher J. 
Published: July 2009

AbstractOver the last ten years, molecular biologists and computer scientists have experimented with various artificial intelligence techniques, notably knowledge based and expert systems, qualitative simulation, natural language processing and various machine learning techniques. These techniques have been applied to problems in molecular data analysis, construction of advanced databases and modelling of biological systems. Practical results are now being obtained, notably in the representation and recognition of genetically significant structures, the assembly of genetic maps and prediction of the structure of complex molecules such as proteins. The paper outlines the principal methods used, surveys the findings to date, and identifies promising trends and current limitations.
Case-based reasoning: A review
Authors: Watson Ian , Marir Farhi 
Published: July 2009

AbstractCase-Based Reasoning (CBR) is a relatively recent problem solving technique that is attracting increasing attention. However, the number of people with first-hand theoretical or practical experience of CBR is still small. The main objective of this review is to provide a comprehensive overview of the subject to people new to CBR. The paper outlines the development of CBR in the US in the 1980s. It describes the fundamental techniques of CBR and contrasts its approach to that of model-based reasoning systems.1A critical review of currently available CBR software tools is followed by descriptions of CBR applications both from academic research and, in more detail, three CBR systems that are presently being used commercially. Each of the three commercial case studies highlights features that made CBR particularly suitable for the application. Moreover, the last case study describes a development methodology for implementing CBR systems. The paper concludes with a research agenda for CBR. A detailed categorized bibliography of CBR research is provided in a companion paper (Marir & Watson, 1994).
Hybrid case-based reasoning
Authors: Hunt John , Miles Roger 
Published: July 2009

AbstractThis paper reviews a number of hybrid Case-Based Reasoning (CBR) systems. These systems are hybrid because the CBR components cooperate with one or more “co-reasoners” which employ a different type of reasoning strategy (e.g. qualitative simulation, constraint satisfaction, etc.). In this paper, we propose that CBR is in fact an inherently hybrid process. We review a number of systems and identify three classes of architecture which have been used for hybrid systems. We believe that to successfully exploit a co-reasoner within a CBR system it is necessary to analyse where, when, why and how the information provided by the co-reasoner will be used. We propose the KADS methodology as a suitable way of performing such an analysis and illustrate its use by example. We conclude by considering the control issues associated with the construction of hybrid CBR systems. We review the requirements of such systems and consider how well the two existing cooperation architectures match those requirements.
Cognitive expertise research and knowledge engineering
Authors: Bolger Fergus 
Published: July 2009

AbstractThis paper is a review of research into cognitive expertise. The review is organized in terms of a simple model of the knowledge and cognitive processes that might be expected to be enhanced in experts relative to non-experts. This focus on cognitivecompetenceunderlying expert performance permits the identification of skills and knowledge that we might wish to capture and model in expert systems. The competence perspective also indicates areas of weakness in human experts. In these areas, we might wish to support or replace the expert with, for example, a normative system rather than attempting to model his or her knowledge.
Verification and validation of knowledge-based systems with formal specifications
Authors: Meseguer Pedro , Preece Alun D. 
Published: July 2009

AbstractThis paper examines how formal specification techniques can support the verification and validation (V&V) of knowledge-based systems. Formal specification techniques provide levels of description which support both verification and validation, and V&V techniques feed back to assist the development of the specifications. Developing a formal specification for a system requires the prior construction of a conceptual model for the intended system. Many elements of this conceptual model can be effectively used to support V&V. Using these elements, the V&V process becomes deeper and more elaborate, and it produces results of a better quality compared with the V&V activities which can be performed on systems developed without conceptual models. However, we note that there are concerns in using formal specification techniques for V&V, not least being the effort involved in creating the specifications.
Formal specification languages in knowledge and software engineering
Authors: Fensel Dieter 
Published: July 2009

AbstractDuring the last few years, a number of formal specification languages for knowledge-based systems (KBS) have been developed. Characteristics of such systems are a complex knowledge base and an inference engine which uses this knowledge to solve a given problem. Languages for KBS have to cover both these aspects. They have to provide a means to specify a complex and large amount of knowledge and they have to provide a means to specify the dynamic reasoning behaviour of a KBS. Nevertheless, KBS are just a specific type of software system. Therefore, it seems quite natural to compare formal languages for specifying KBS with formal languages which were developed by the software community for specifying software systems. That is the subject of this paper.
An integrated approach for different attribute types in nearest neighbour classification
Authors: Liu W. Z. 
Published: July 2009

AbstractThe basic nearest neighbour algorithm works by storing the training instances and classifying a new case by predicting that it has the same class as its nearest stored instance. To measure the distance between instances, some distance metric needs to be used. In situations when all attributes have numeric values, the conventional nearest neighbour method treats examples as points in feature spaces and uses Euclidean distance as the distance metric. In tasks with only nominal attributes, the simple “over-lap” metric is usually used. To handle classification tasks that have mixed types of attributes, the twodifferentmetrics are simply combined. Work by researchers in the machine learning field has shown that this approach performs poorly. This paper attempts to study a more recently developed distance metric and show that this metric is capable of measuring the importance of different attributes. With the use of discretisation for numeric-valued attributes, this method provides an integrated way in dealing with problem domains with mixtures of attribute types. Through detailed analyses, this paper tries to provide further insights into the understanding of nearest neighbour classification techniques and promote further use of this type of classification algorithm.
Declarative specifications
Authors: Fuchs Norbert E. , Robertson David 
Published: July 2009

AbstractDeriving formal specifications from informal requirements is extremely difficult since one has to overcome the conceptual gap between an application domain and the domain of formal specification methods. To reduce this gap we introduce application-specific specification languages, i.e., graphical and textual notations that can be unambiguously mapped to formal specifications in a logic language. We describe a number of realised approaches based on this idea, and evaluate them with respect to their domain specificity vs. generality.
Logic engineering in medicine
Authors: Lucas Peter J. F. 
Published: July 2009

AbstractThe safety-critical nature of the application of knowledge-based systems to the field of medicine requires the adoption of reliable engineering principles with a solid foundation for their construction. Logical languages with their inherent, precise notions of consistency, soundness and completeness provide such a foundation, thus promoting scrupulous engineering of medical knowledge. Moreover, logic techniques provide a powerful means for getting insight into the structure and meaning of medical knowledge used in medical problem solving. Unfortunately, logic is currently only used on a small scale for building practical medical knowledge-based systems. In this paper, the various approaches proposed in the literature are reviewed, and related to the various types of knowledge and problem solving employed in the medical field. The appropriateness of logic for building medical knowledge-based expert systems is further motivated.
Provenance and post-depositional low-temperature evolution of the James Ross Basin sedimentary rocks (Antarctic Peninsula) based on fission track analysis
Authors: Svojtka Martin , Nývlt Daniel , Murakami Masaki , Vávrová Jitka , Filip Jiří , Mixa Petr 
Published: July 2009

AbstractZircon and apatite fission track (AFT) thermochronology was applied to the James Ross Basin sedimentary rocks from James Ross and Seymour islands. The probable sources of these sediments were generated in Carboniferous to Early Paleogene times (∼315 to 60 Ma). The total depths of individual James Ross Basin formations are discussed. The AFT data were modelled, and the thermal history model was reconstructed for samples from Seymour Island. The first stage after a period of total thermal annealing (when the samples were above 120°C) involved Late Triassic cooling (∼230 to 200 Ma) and is followed by a period of steady cooling through the whole apatite partial annealing zone (PAZ, 60–120°C) to minimum temperature in Paleocene/Early Eocene. The next stage was the maximum burial of sedimentary rocks in the Eocene (∼35 Ma, 1.1–1.8 km) and the final cooling and uplift of Seymour Island sedimentary rocks at ∼35 to 20 Ma.
A unifying perspective on personality pathology across the life span: Developmental considerations for the fifth edition of theDiagnostic and Statistical Manual of Mental Disorders
Authors: Tackett Jennifer L. , Balsis Steve , Oltmanns Thomas F. , Krueger Robert F. 
Published: July 2009

AbstractProposed changes in the fifth edition of theDiagnostic and Statistical Manual of Mental Disorders(DSM-V) include replacing current personality disorder (PD) categories on Axis II with a taxonomy of dimensional maladaptive personality traits. Most of the work on dimensional models of personality pathology, and on personality disorders per se, has been conducted on young and middle-aged adult populations. Numerous questions remain regarding the applicability and limitations of applying various PD models to early and later life. In the present paper, we provide an overview of such dimensional models and review current proposals for conceptualizing PDs inDSM-V. Next, we extensively review existing evidence on the development, measurement, and manifestation of personality pathology in early and later life focusing on those issues deemed most relevant for informingDSM-V. Finally, we present overall conclusions regarding the need to incorporate developmental issues in conceptualizing PDs inDSM-Vand highlight the advantages of a dimensional model in unifying PD perspectives across the life span.
Predictors of withdrawal: Possible precursors of avoidant personality disorder
Authors: Eggum Natalie D. , Eisenberg Nancy , Spinrad Tracy L. , Valiente Carlos , Edwards Alison , Kupfer Anne S. , Reiser Mark 
Published: July 2009

AbstractRelations of avoidant personality disorder (AvPD) with shyness and inhibition suggest that a precursor of AvPD is withdrawal. Using a sample of 4.5- to 7-year-olds studied four times, 2 years apart, four and three classes of children differing in trajectories of mother- and teacher-reported withdrawal, respectively, were identified. Mothers and teachers generally did not agree on children's trajectories but the pattern of findings in the two contexts did not differ markedly. The mother-identified high and declining withdrawal class, in comparison with less withdrawn classes, and the teacher-identified high and declining class compared with low withdrawal classes, were associated with relatively high levels of anger and low levels of attentional control and resiliency. The mother-identified moderate and increasing withdrawal class was distinguished from less problematic withdrawal classes by higher anger, lower resiliency, and sometimes, lower attentional control. The teacher-identified low and increasing withdrawal class was distinguished from less problematic withdrawal classes by lower resiliency and lower attentional control. Findings are discussed in terms of the developmental precursors to social withdrawal and avoidant behavior.
Childhood personality pathology: Dimensional stability and change
Authors: de Clercq Barbara , van Leeuwen Karla , van den Noortgate Wim , de Bolle Marleen , de Fruyt Filip 
Published: July 2009

AbstractStudies on the developmental course of personality disorders have suggested that adult personality disorders enclose both features with a natural plasticity over time, as well as stable components represented by underlying trait dimensions. The current study broadens this dimensional stability perspective toward an earlier developmental stage, and describes with different indices of stability the longitudinal behavior of basic childhood maladaptive trait dimensions in a community sample of 477 Flemish children. The results underscore structural, rank-order, and within-person stability for the disagreeableness, emotional instability, introversion, and compulsivity dimensions and suggest a similar maturation principle as has been proposed for adults. Individual growth curve analyses indicate that children's maladaptive trait scores generally decrease as they grow older, with a smaller decline for high-scoring individuals. Childhood maladaptive traits and general psychopathology dimensions show similar longitudinal patterns in terms of shape and change over time, supporting a spectrum conceptualization of Axis I related pathology and personality disorder precursors at young age. The implications of these findings for a developmental perspective on dimensional conceptualizations of personality disorders are discussed.