Showing papers in "Knowledge Based Systems in 1997"
TL;DR: An algorithm and an implementation are described by which generalized rules for simplification are automatically induced from annotated training material using a novel partial parsing technique which combines constituent structure and dependency information.
Abstract: Long and complicated sentences pose various problems to many state-of-the-art natural language technologies. We have been exploring methods to automatically transform such sentences in order to make them simpler. These methods involve the use of a rule-based system, driven by the syntax of the text in the domain of interest. Hand-crafting rules for every domain is time-consuming and impractical. The paper describes an algorithm and an implementation by which generalized rules for simplification are automatically induced from annotated training material using a novel partial parsing technique which combines constituent structure and dependency information. The algorithm described in the paper employs example-based generalizations on linguistically motivated structures.
166 citations
TL;DR: This paper outlines the pipeline schedule generation problem, where the task is to generate a pumping schedule for a single-source multiple-destinations oil pipeline carrying multiple products, and describes an approach based on heuristic search, which has been successfully implemented and is in use.
Abstract: Resource scheduling problems are increasingly being solved using AI techniques. Solving real-life versions of these problems demands the ability to model a range of constraints and, at the same time, to be flexible enough to make revisions to these constraints. In this paper, we outline the pipeline schedule generation problem, where the task is to generate a pumping schedule for a single-source multiple-destinations oil pipeline carrying multiple products. The schedule must take into account product availability and requirements while satisfying a wide variety of domain constraints, including tankage constraints, product sequencing constraints, quality control constraints, delivery constraints, etc. We describe an approach based on heuristic search, which we have adopted for solving it. The system has been successfully implemented and is in use.
85 citations
TL;DR: The editor is found to be a very useful tool for recording the creative thinking process, and can be used afterwards for interpreting the specification which is a result of the requirement analysis.
Abstract: KJ method, which was developed for creative thinking, uses cards for making a conceptual map from brainstorming. A card-handling editor for supporting the method is presented and was used for analysing requirements of software. The most important effect of using the editor is that not only the relations between the brainstormed matters but also what is lacking in them can be found. The editor is found to be a very useful tool for recording the creative thinking process, and can be used afterwards for interpreting the specification which is a result of the requirement analysis.
53 citations
TL;DR: Aspects of creativity research are explored and two case studies by the author are described and the implications of knowledge-intensive work including visualisation and collaboration for computer support are discussed.
Abstract: This paper is concerned with research into creativity and how it might inform our understanding of knowledge-based computer support. Aspects of creativity research are explored and two case studies by the author are described. The implications of knowledge-intensive work including visualisation and collaboration for computer support are discussed. Finally, future research directions that combine the aims, objectives and techniques of both the artificial intelligence and human-computer interaction communities are outlined.
49 citations
TL;DR: A conceptual framework of creativity in the context of everyday practice is developed that explores new role distributions between people and computers based on theories that view design as reflection-in-action and breakdowns as opportunities for learning and creativity.
Abstract: Much of our intelligence and creativity results from the collective memory of communities of practice and of the artifacts and technology surrounding them. Rather than studying individual creativity in isolation, we have developed a conceptual framework of creativity in the context of everyday practice — where design activities prevail and learning is constantly required. The conceptual framework explores new role distributions between people and computers based on theories that view design as reflection-in-action and breakdowns as opportunities for learning and creativity. We use an example from the domain of multimedia information design to illustrate how creativity is supported by domain-oriented design environments. The paper describes the mechanisms, architectures and processes underlying these environments.
30 citations
TL;DR: This paper describes a system that supports creative design in which fragments of requirements and design parameters are arranged as the result of knowledge processing.
Abstract: This paper describes a system that supports creative design. The system presents the user with a "concept space" in which fragments of requirements and design parameters are arranged as the result of knowledge processing. Interacting with the concept space, the designer can apply design strategies which are different from those used in daily design, which may lead to creative design.
27 citations
TL;DR: An integrated system in which a knowledge-based decision support system is integrated with a multilayer artificial neural network for urban planning is presented, which achieves improvements in the implementation of each as well as increases the scope of the application.
Abstract: More applications that integrate knowledge-based decision support systems and artificial neural networks are starting to appear, and interest in such integrated systems is growing rapidly. The paper presents an integrated system in which a knowledge-based decision support system is integrated with a multilayer artificial neural network for urban planning. By integrating decision support systems, knowledge-based systems and artificial neural networks, the system achieves improvements in the implementation of each as well as increases the scope of the application. This approach is very rewarding in its synergism of three technologies to solve complex problems. The paper discusses the structure of the integrated system, as well as providing an example of application.
17 citations
TL;DR: A Radiotherapy Treatment Planning Learning Environment (called RATAPLAN), which incorporates an interface intelligent agent to support training of Simulation Technologists and Radiation Physicists in this knowledge domain and promotes the collaboration between novice and expert practitioners in Radi Therapy Treatment Planning.
Abstract: The main aim of this paper is to discuss the design issues and implications that relate to the use of software agents in Training Systems We have designed and implemented a Radiotherapy Treatment Planning Learning Environment (called RATAPLAN), which incorporates an interface intelligent agent to support training of Simulation Technologists and Radiation Physicists in this knowledge domain The learning environment consists of an interactive simulation The interface agent (called Consulta) acts both as demonstrator and assistant to the users The paper describes in depth the agent's architecture and illustrates the agentᑛuser interaction and communication With Consulta we promote the collaboration between novice and expert practitioners in Radiotherapy Treatment Planning
14 citations
TL;DR: A computer-assisted method of consensus making for creative and cooperative problem solving and a major concern is to inspire the creative thinking of the participants by introducing some creative thinking methods into the consensus-making process.
Abstract: This paper proposes a computer-assisted method of consensus making for creative and cooperative problem solving. The creative problem solving we treat has a process which constructs appropriate evaluation structure interactively and chooses the optimal alternative plan rationally. In this problem solving, the problem is complicated because each participant in the group has his own sense of value which may be different from the others'. We expect the problem can be solved effectively by integrating various techniques such as creative techniques, decision support techniques and groupware techniques. Our major concern is to inspire the creative thinking of the participants by introducing some creative thinking methods into the consensus-making process. In this paper, our consensus-making support method and its implementation example are described.
13 citations
TL;DR: In the framework, a mechanism of situation representation is used to model temporally changing problem-solving states and interactions within the environment and a heuristic constraint satisfaction model is exploited as a means of decision-making with incomplete information.
Abstract: Multi-agent technology has emerged as a promising discipline for modeling distributed information system applications. One of such applications is the modeling of cooperative decision systems. The knowledge used in such systems is typically uncertain, heuristic, and temporally changing. In this paper, we propose a framework to model cooperative decision systems. In the framework, a mechanism of situation representation is used to model temporally changing problem-solving states and interactions within the environment. A heuristic constraint satisfaction model is exploited as a means of decision-making with incomplete information. A cooperation protocol based on the situation mechanism and the heuristic constraint model is designed.
13 citations
TL;DR: The facilities of the system are explained, how to use it is described, and some examples of their use are described.
Abstract: An interactive computer system for supporting the emergent stages (or upper streams) in human intellectual activities has been developed In the system it is intended to integrate facilities for supporting generation, collection, organisation, and presentation of ideas and advising on the divergence and convergence of the ideas This paper explains the facilities of the system and how to use it, and describes some examples of their use
TL;DR: A user-friendly system containing an operational suite of tools that support intelligence data processing, data visualization, historical analysis, situation assessment and predictive analysis, and expert system tools is discussed.
Abstract: We discuss a user-friendly system containing an operational suite of tools that support intelligence data processing, data visualization, historical analysis, situation assessment and predictive analysis. The tools facilitate the study of events as a function of time to determine situational patterns. To support this analysis, the system has various data displays (e.g., timelines, maps charts, and tables) a historical event database, query capabilities, and expert system tools. The expert system tools analyze temporal information, predict future events, and explain decisions visually and textually. The tools are currently installed in several military commands and intelligence agencies supporting analysis ranging from strategic C3 to counter drug.
TL;DR: RICAD differs from other CBR systems as, in most cases, in addition to the use of the statistical function, it has to repeat its reasoning process until an adequate number of cases are collected to calculate the answer.
Abstract: Most case-based reasoning (CBR) systems concentrate on retrieving cases which are most similar to a case at hand. When a similar case is found, the system will proceed to adapt (or modify) this solution to solve the case at hand. This method of problem solving cannot be easily applied in our real-world problem domain (i.e. insurance). In this domain, sufficient number of similar cases have to be retrieved so that the system could confidently calculate the final solution. More than one similar case must be retrieved due to the fact that most of the cases which are similar to the one at hand almost always contain inconsistent results. This paper describes a CBR system called risk cost adviser (RICAD) which applies a statistical function in order to propose a reliable answer. RICAD differs from other CBR systems as, in most cases, in addition to the use of the statistical function, it has to repeat its reasoning process until an adequate number of cases are collected to calculate the answer.
TL;DR: A system for facilitating the industrial designer's divergent thinking process in which he often falls into his established thinking way and come to a dead end on the way of generating fresh ideas is presented.
Abstract: The paper presents a system for facilitating the industrial designer's divergent thinking process in which he often falls into his established thinking way and come to a dead end on the way of generating fresh ideas. The system uses two methods to free the designer from his own established way of thinking. The first method classifies the designer's idea sketches from different viewpoints, and finds new concepts from the intersections of the classified groups. The second method finds a meta-concept of the classifications to arrive at new classification concepts. The system has been used in several students' design projects and has produced good results.
TL;DR: A complex object-based knowledge representation whose key feature is that the contents of all the knowledge-base, including the design process, are expressed only by objects and classes is presented.
Abstract: Our main concern is to identify the major issues related to representing and controlling design knowledge for large scale structures such as ships in routine parametric redesign. In our view, the most difficult problems can occur in the complexity of representing the design object and the need for a formal way of describing rules for classification that play the most important role in providing design expertise used for the structural design of ships. Hence, we present a complex object-based knowledge representation whose key feature is that the contents of all the knowledge-base, including the design process, are expressed only by objects and classes. Also, we devise an inference mechanism, called the CORE (complex object-based inference) mechanism, that is based on a hypothesis-object. To illustrate how the CORE mechanism works in a realistic domain, design systems for the deck structure and midship section of bulk cargo ships are implemented, and some running examples are presented.
TL;DR: The performance of the proposed neural network architecture as compared to a fully connected multi-layer perceptron and any randomly connected architecture with same average connectivity in terms of proper classification and good generalization has been studied by simulation with sonar data collected from underwater target classification problems using sonar signals.
Abstract: A fractal connection structure among different layers of multi-layer neural network has been proposed here and its computational performance as a pattern classifier has been studied in comparison to a more conventional and widely used multi-layer perceptron classifier (MLP). A good classifier should consider two aspects: correct classification and perfect generalization. After an appropriate learning period, a good classifier should be able to classify any unknown sample outside the training set with the same accuracy as any sample from the training set. The performance of the proposed neural network architecture as compared to a fully connected multi-layer perceptron and any randomly connected architecture with same average connectivity in terms of proper classification and good generalization has been studied by simulation with sonar data collected from underwater target classification problems using sonar signals. It was found that with equal average connectivity, a fractally connected net performs better than a randomly connected net, and with the same number of neurons a fractally connected net performs better than the fully connected net.
TL;DR: This paper proposes a formal approach to integrate connectionist and symbolic systems where as a symbolic system the system is considered a (logic) rule-based system and provides an integrated framework to represent and process heterogeneous knowledge.
Abstract: Heterogeneous knowledge representation allows the combination of several knowledge representation techniques. For instance connectionist and symbolic systems are two different computational paradigms and knowledge representations. Unfortunately, the integration of different paradigms and knowledge representations is not easy and very often is informal. In this paper, we propose a formal approach to integrate these two paradigms where as a symbolic system we consider a (logic) rule-based system. The integration is operated at language level between neural networks and rule languages. The formal model that allows the integration is based on constraint logic programming and provides an integrated framework to represent and process heterogeneous knowledge. In order to achieve this we define a new language that allows us to express and model in a natural and intuitive way the above issues together with the operational semantics.
TL;DR: The thesis is that commonsense behaviour is essentially underpinned by tacit knowledge, and the basic arguments hinge on the distinctions between tacit knowledge and propositionizable knowledge.
Abstract: Symbolic expert systems have been developed during the last three decades to model knowledge-based human intelligent behaviour. A general criticism of such expert systems is that they lack commonsense. But there is little consensus among AI workers on what constitutes commonsense. In this paper a characterization of commonsense is attempted. The limitations and open problems relating to current approaches to expert systems design are discussed. In addition, open problems that need to be studied to adequately model commonsense behaviour are discussed. Our basic arguments hinge on the distinctions between tacit knowledge and propositionizable knowledge. The thesis is that commonsense behaviour is essentially underpinned by tacit knowledge.
TL;DR: One of the main objectives of the Abduction Machine Project is to establish a new view of abduction, which plays a crucial role in creative processes, by combining the experientialist views on human knowledge and architectural space design methodologies.
Abstract: The Abduction Machine Project is in progress at RACE (Research into Artifacts, Centre for Engineering) of the University of Tokyo. In this project, we are focusing on the creative process of human reasoning, referred to as abduction (hypothesis generation). The Abduction Machines are experiential apparatus to embody and describe the process of abduction. One of the main objectives of the Abduction Machine Project is to establish a new view of abduction, which plays a crucial role in creative processes, by combining the experientialist views on human knowledge and architectural space design methodologies.
TL;DR: Inspired by linear logic, or logic of resources, a language for knowledge-based systems of resources is proposed, which can process state space models of systems represented by Petri nets or their subclasses such as marked graphs and state machines.
Abstract: It appears that classical logic is not suitable for the representation and reasoning about knowledge of disposable resources. The major difference between reasoning about disposable resources and classical logic is that once a disposable resource is used to produce something, it is not available any more; but a formula of classical logic can be repeatedly used in deduction. Inspired by linear logic, or logic of resources, we propose a language for knowledge-based systems of resources, which can process state space models of systems represented by Petri nets or their subclasses such as marked graphs and state machines. It can serve as a modeling tool for various engineering and social science problems of resource allocations.
TL;DR: The analyses and experiments in this paper suggest that inference guiding has a substantial influence on effectiveness and efficiency of entire inference process in many knowledge-based systems and the heuristic which was developed by Wang and Vande Vate may improve inference guiding significantly at an acceptable cost.
Abstract: In many applications of knowledge-based systems, initial facts and data are not sufficient to reach a pertinent result and more facts are needed to proceed the logic inference. What additional information is to be selected and how to select the information comprise the inference guiding problem. The analyses and experiments in this paper suggest that: (1) inference guiding has a substantial influence on effectiveness and efficiency of entire inference process in many knowledge-based systems; (2) inference guiding strategies on random bases, as used in many knowledge-based systems on the market, are not effective; and (3) the heuristic which was developed by Wang and Vande Vate may improve inference guiding significantly at an acceptable cost.