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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 4 (1989), S. 339-345 
    ISSN: 0885-6125
    Keywords: Generic tasks ; learning ; knowledge acquisition ; task-structure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract One of the old saws about learning in AI is that an agent can only learn what it can be told, i.e., the agent has to have a vocabulary for the target structure which is to be acquired by learning. What this vocabulary is, for various tasks, is an issue that is common to whether one is building a knowledge system by learning or by other more direct forms of knowledge acquisition. I long have argued that both the forms of declarative knowledge required for problem solving as well as problem-solving strategies are functions of the problem-solving task and have identified a family of generic tasks that can be used as building blocks for the construction of knowledge systems. In this editorial, I discuss the implication of this line of research for knowledge acquisition and learning.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 4 (1989), S. 339-345 
    ISSN: 0885-6125
    Keywords: Generic tasks ; learning ; knowledge acquisition ; task-structure
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract One of the old saws about learning in AI is that an agent can only learn what it can be told, i.e., the agent has to have a vocabulary for the target structure which is to be acquired by learning. What this vocabulary is, for various tasks, is an issue that is common to whether one is building a knowledge system by learning or by other more direct forms of knowledge acquisition. I long have argued that both the forms of declarative knowledge required for problem solving as well as problem-solving strategies are functions of the problem-solving task and have identified a family of generic tasks that can be used as building blocks for the construction of knowledge systems. In this editorial, I discuss the implication of this line of research for knowledge acquisition and learning.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Knowledge Acquisition 1 (1989), S. 139-162 
    ISSN: 1042-8143
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Computer Science
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Journal of Chromatography B: Biomedical Sciences and Applications 276 (1983), S. 237-242 
    ISSN: 0378-4347
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Amsterdam : Elsevier
    Journal of Chromatography B: Biomedical Sciences and Applications 309 (1984), S. 403-408 
    ISSN: 0378-4347
    Source: Elsevier Journal Backfiles on ScienceDirect 1907 - 2002
    Topics: Chemistry and Pharmacology
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Oxford, UK : Blackwell Publishing Ltd
    Computational intelligence 8 (1992), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Boston, USA and Oxford, UK : Blackwell Publishers Inc.
    Computational intelligence 18 (2002), S. 0 
    ISSN: 1467-8640
    Source: Blackwell Publishing Journal Backfiles 1879-2005
    Topics: Computer Science
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Engineering with computers 16 (2000), S. 162-177 
    ISSN: 1435-5663
    Keywords: Keywords:Causal reasoning; Compositional modeling; Device ontology; Device simulation; Functional reasoning; Functional representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Technology
    Notes: We explore the meanings of the terms ‘structure’, ‘behaviour’, and, especially, ‘function’ in engineering practice. Computers provide great assistance in calculation tasks in engineering practice, but they also have great potential for helping with reasoning tasks. However, realising this vision requires precision in representing engineering knowledge, in which the terms mentioned above play a central role. We start with a simple ontology for representing objects and causal interactions between objects. Using this ontology, we investigate a range of meanings for the terms of interest. Specifically, we distinguish between function as effect on the environment, and a device-centred view of device function. In the former view, function is seen as an intended or desired role that an artifact plays in its environment. We identify an important concept called mode of deployment that is often left implicit, but whose explicit representation is necessary for correct and complete reasoning. We discuss the task of design and design verification in this framework. We end with a discussion that relates needs in the world to functions of artifacts created to satisfy the needs.
    Type of Medium: Electronic Resource
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Research in engineering design 1 (1989), S. 75-86 
    ISSN: 1435-6066
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics , Technology
    Notes: Abstract We develop atask-structure for design problem-solving. The task-structure of a complex problemsolving activity such as design is a hierarchical organization of subtasks. For each task in the task-structure, we can then proceed to investigate whatmethods may be available, and what knowledge and inference requirements each of these methods have. Some of the methods may be domain-specific, some of them more generic in character, some may involve traditional computational techniques, and some others may involve searching in a problem space for solutions to the task. However, this systematic process of identifying tasks, methods, and subtasks will help us to see how design as a general problem is solved not by one method or technique but by an opportunistic exploitation of whatever methods are available (i.e., theknowledge required for using a method is available) to help accomplish a subtask. Thus, in principle, very different methods and knowledge can be brought into play in as flexible a way as applicable. For design problem-solving, we provide such an analysis for a family of design methods that we callpropose-verify-critique-modify methods. We end with remarks about how these methods can be flexibly integrated in a control structure that matches the subtasks with methods for which knowledge is available.
    Type of Medium: Electronic Resource
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  • 10
    Publication Date: 1975-12-01
    Print ISSN: 0031-3203
    Electronic ISSN: 1873-5142
    Topics: Computer Science
    Published by Elsevier
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