Knowledge-based Problem Solving Research Articles

WITHDRAWN: Knowledge-Based Problem Solving in Physical Product Development – A Methodological Review

WITHDRAWN: Knowledge-Based Problem Solving in Physical Product Development – A Methodological Review

Promoting Knowledge-based Creative Problem Solving

Promoting Knowledge-based Creative Problem Solving

A Knowledge-based Problem Solving and Automated Document Writing System for E-filing in the Summary Order Procedure

A Knowledge-based Problem Solving and Automated Document Writing System for E-filing in the Summary Order Procedure

A Simulator Experiment Investigating the Effects of Masked Indicators in a NPP Emergency Control Task: Scenario and Design

This paper describes the scenario and participants of a simulator experiment investigating the performance of nuclear power plant (NPP) control room crews in a realistic accident scenario where multiple failures lead to masking of relevant diagnostic information. These conditions challenge emergency operating procedures and require crews to engage in knowledge-based problem solving. The study placed particular emphasis on generating rich operational descriptions of crew behavior and performance-shaping factors.

Extracting focused knowledge from the semantic web

Ontologies are increasingly being recognized as a critical component in making networked knowledge accessible. Software architectures which can assemble knowledge from networked sources coherently according to the requirements of a particular task or perspective will be at a premium in the next generation of web services. We argue that the ability to generate task-relevant ontologies efficiently and relate them to web resources will be essential for creating a machine-inferencable “semantic web”. The Internet-based multi-agent problem solving (IMPS) architecture described here is designed to facilitate the retrieval, restructuring, integration and formalization of task-relevant ontological knowledge from the web. There are rich structured and semi-structured sources of knowledge available on the web that present implicit or explicit ontologies of domains. Knowledge-level models of tasks have an important role to play in extracting and structuring useful focused problem-solving knowledge from these web sources. IMPS uses a multi-agent architecture to combine these models with a selection of web knowledge extraction heuristics to provide clean syntactic integration of ontological knowledge from diverse sources and support a range of ontology merging operations at the semantic level. Whilst our specific aim is to enable on-line knowledge acquisition from web sources to support knowledge-based problem solving by a community of software agents encapsulating problem-sloving inferences, the techniques described here can be applied to more general task-based integration of knowledge from diverse web sources, and the provision of services such as the critical comparison, fusion, maintenance and update of both formal informal ontologies.

Knowledge-based problem solving: an approach to health assessment

Improving health care assessment through the implementation of advanced technologies has been a concern of medical professionals as well as computer scientists in China. Many believe that advanced technology can improve Chinese people's access to health service and improve service quality. This belief has encouraged the application of technology to health services. One of the earliest expert systems developed in the late 70s in China was for the diagnosis and treatment of hepatitis. Since then Chinese researchers have developed numerous knowledge based systems that have been implemented in various areas. In this study, a hybrid knowledge-based system developed in China is introduced. The system which integrates a deductive rule-based reasoning system, an inductive case-based reasoning (CBR) system, and a quantitative model-based reasoning (MBR) system was applied to diagnose and assess AIDS risky patients. The system was tested using actual data, and results are encouraging.

A Multidimensional and Multigranular Model of Time for Medical Knowledge-Based Systems

In temporal reasoning there are two interrelated issues; how to model time per se and how to model occurrences. In medical temporal reasoning the need for multiple granularities and multiple conceptual temporal contexts arises in relation to a model of time. Some occurrence can then be expressed with respect to different temporal contexts. This paper presents a multidimensional and multigranular model of time for knowledge-based problem solving, primarily for medical applications. Both the conceptual issues and the design issues underlying the implementation of the proposed model are discussed. The presented model of time has been developed in the context of a time ontology for medical knowledge engineering, whose principal primitives are the time-axis and the time-object. The notion of a time-axis constitutes the primitive for the proposed model of time, while the notion of a time-object aims to integrate time with other essential forms of knowledge, such as structural and causal knowledge, in the expression of different types of occurrences, thus resulting in the integral embodiment of time in such occurrences. The notion of a time-object and the overall ontology of occurrences is given only a cursory mention in this paper. The focus of the paper is the time model. More specifically, the paper presents the notion of a time-axis in the context of the overall time ontology and discusses at length the two classes of time-axes, namely the atomic axes and the spanning axes. The assertion language which has been developed, for the entire ontology, for the expression of axioms (deductive rules and integrity constraints), attribute constraints and propagation methods is presented and illustrated. The implementation of the time model in terms of a layered object-based system is also presented.

An ecological interface for supervisory control of BWR nuclear power plants

An ecological interface design was applied to implement support functions for the operator's direct perception and analytical reasoning in the development of an intelligent man-machine system for BWR nuclear power plants. An abstraction-aggregation functional hierarchy representation of the work domain is one basis of the ecological interface design. Another basis is the concept of the level of cognitive control. The former was mapped into the interface to externalize the operator's normative mental model of the plants, which will reduce his/her cognitive work load and support knowledge-based problem solving.

A multidimensional knowledge structure

Expert system has gone through several shifts in view, from search-based to knowledge-based problem solving and from knowledge transfer to knowledge modeling. However, knowledge is still mostly treated informally. There are widely different opinions on its nature. This paper first attempts to characterize knowledge contents within the context of knowledge level and then proposes a knowledge structure. Four characteristics of knowledge, namely particularity, specificity, bipolarity, and orthogonality, are identified. They form the components of a multidimensional knowledge structure that constitutes a static spatial organization of knowledge. These components are related together through multiple levels of details and multiple system views. The proposed structure creates a taxonomy for classifying knowledge. It brings chaos to order by giving meanings to the phenomenon of diverse opinions on knowledge.

Automated CAD protective packaging design

Protective packaging forms an important integral part in the materials handling process of ensuring that goods are transferred ‘safely’ from the source to the point of use. This paper focuses on the ‘procedural’ design practices for protective packaging which are predominantly manual and involves the use of implicit design rules, and is therefore amenable to design automation efforts. PROPACK, a protective packaging CAD software program for expanded styropor material has been developed by coupling various existing commercial software packages for drafting, analysis, database management, and knowledge based problem solving and consultation. In so doing, it exploits the well-proven and stable features of these tools for the different activities and stages of design. The coupling of the various packages to form an integrated system is achieved either by the creation of task specific interfaces between packages, or by making use of existing interfaces provided in some of these packages. The relative merits of adopting this approach are also discussed.

Capturing intelligence as a reusable framework for manufacturing decision processes

A reusable framework consisting of hierarchical knowledge representation, preliminary design, iterative modification, four information flow and reasoning paths, and solution validation is conceived as a common substrate for addressing multiple components in manufacturing decision processes. The problems are represented in a state-space framework. An investment is made to design a rich representational scheme and to discriminate the promising solution states by utilizing its many implicit constraints in contrast to investing in heuristics operating on a more simplified representation of the problem. Although isolated segments of the described framework (e.g. hierarchical problem solving, abstraction) have been previously mentioned in knowledge-based problem solving, the framework distinguishes itself by exploring the nature of the interaction of these concepts in actually obtaining end results for manufacturing problems. Although hard to quantify, it is stated that the involved ‘intelligence’ from the manu...

A personal view of expert systems: Looking back and looking ahead

Expert system has gone through several shifts in view, from search-based to knowledge-based problem solving and from knowledge transfer to knowledge modeling. However, knowledge is still mostly treated informally. There are widely different opinions on its nature. This paper first attempts to characterize knowledge contents within the context of knowledge level and then proposes a knowledge structure. Four characteristics of knowledge, namely particularity, specificity, bipolarity, and orthogonality, are identified. They form the components of a multidimensional knowledge structure that constitutes a static spatial organization of knowledge. These components are related together through multiple levels of details and multiple system views. The proposed structure creates a taxonomy for classifying knowledge. It brings chaos to order by giving meanings to the phenomenon of diverse opinions on knowledge.

Adapting the memory recall paradigm to evaluate interfaces

This paper is concerned with developing a methodology for evaluating the effectiveness with which an interface supports knowledge-based problem solving. The memory recall paradigm pioneered by De Groot (1965) is suggested as a plausible methodology. A thorough review of the empirical findings in the literature and the various theoretical accounts of the chunking phenomenon was conducted, and a novel integrative account of chunking was proposed. Based on this description of the psychological processes associated with chunking, it was concluded that a variation of the memory recall methodology can indeed be used to evaluate interface transparency. The paper ends by making specific recommendations for adapting the paradigm to the characteristics of the process control environment.

From numbers to symbols to knowledge structures: artificial intelligence perspectives on the classification task

The general information-processing task of classification is considered and reviewed from the perspectives of the knowledge-based-reasoning, pattern-recognition, and connectionist paradigms in artificial intelligence, paying special attention to knowledge-based classificatory problem solving. The authors trace the evolution of the mechanisms for classification as the computational complexity of the problem increases, from numerical parameter-setting schemes, through those using intermediate abstractions and then relations between symbols, and finally to complex symbolic structures that explicitly incorporate domain knowledge. >

Knowledge-Based Problem Solving

Knowledge-Based Problem Solving

Issues in Knowledge-Based Problem Solving

In knowledge-based problem-solving systems, many problems will be solved by application of general solution plans, each capable of satisfying a class of goal states from a variety of initial states. A range of important issues which must be addressed in the design of such problem-solving systems is discussed. One area of concern deals with the representation, storage, and activation of general solution plans. Another is the efficient coordination of plan executions in circumstances which demand concurrent satisfaction of several goal states. A third area deals with issues related to time: the maintenance over time of the environment in states which allow or facilitate application of general solution plans and the solution of problems under time constraints. A general model within which these issues can be addressed is proposed.