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  • Articles  (10)
  • case-based reasoning
  • Springer  (10)
  • Blackwell Publishers Ltd
  • Oxford University Press
  • 1990-1994  (10)
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  • Articles  (10)
Publisher
  • Springer  (10)
  • Blackwell Publishers Ltd
  • Oxford University Press
Years
Year
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 5 (1994), S. 411-430 
    ISSN: 1572-8145
    Keywords: Process planning ; rotational parts ; case-based reasoning ; feature-based representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: This paper introduces a case-based process planning system PROCASE which generates new process routines through learning from existing process routines. In contrast to traditional rule-based systems, the process planning knowledge of the PROCASE is represented in terms of cases instead of production rules. The planning basically comprises case retrieving and case adaptation rather than chaining applicable rules together to form process plans. The advantages are, first, the system is cheaper to build as it saves the expense of knowledge acquisition. Second, the system is able to advance its knowledge automatically through planning practice. Third, it is robust, because the reasoning is not based on pattern matching but similarity comparison. PROCASE has three modules: the retriever, the adapter and the simulator. It is supported by a feature-based representation scheme which naturally serves as the case indices for case retrieving and adaptation. The retriever uses a similarity metric to retrieve an old case which is the most similar case, among all old ones, to the new case. The adapter is then activated to adapt the process plan of the retrieved case to fit the needs for the new case. The simulator is used to verify the feasibility of the adapted plan. PROCASE is implemented on a Silicon Graphics IRIS workstation using C++ . An example is given to demonstrate how the process routine is generated by the system proposed by the authors.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent manufacturing 2 (1991), S. 137-153 
    ISSN: 1572-8145
    Keywords: Diagnosis ; knowledge acquisition ; acquisition ; knowledge reuse ; case-based reasoning ; object-oriented computing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mechanical Engineering, Materials Science, Production Engineering, Mining and Metallurgy, Traffic Engineering, Precision Mechanics
    Notes: Abstract ODS, object-based Diagnostic System, combines the features found in an object-oriented environment with an intelligent interrogator and can be used to build and execute diagnostic expert systems. ODS is designed to maximally reuse existing knowledge during the acquisition of new knowledge, as well as to reduce omissions and inconsistencies. It incorporates two techniques for making suggestion to the expert, one of which utilizes case-based reasoning.
    Type of Medium: Electronic Resource
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence and law 1 (1992), S. 3-44 
    ISSN: 1572-8382
    Keywords: argument ; case-based reasoning ; mixed paradigm ; statutory interpretation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract We discuss several aspects of legal arguments, primarily arguments about the meaning of statutes. First, we discuss how the requirements of argument guide the specification and selection of supporting cases and how an existing case base influences argument formation. Second, we present,our evolving taxonomy of patterns of actual legal argument. This taxonomy builds upon our much earlier work on ‘argument moves” and also on our more recent analysis of how cases are used to support arguments for the interpretation of legal statutes. Third, we show how the theory of argument used by CABARET, a hybrid case-based/rule-based reasoner, can support many of the argument patterns in our taxonomy.
    Type of Medium: Electronic Resource
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    Artificial intelligence and law 2 (1993), S. 83-111 
    ISSN: 1572-8382
    Keywords: Issue spotting ; torts ; case-based reasoning ; knowledge representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Law
    Notes: Abstract For any system that uses previous experience to solve problems in new situations, it is necessary to identify the features in the situation that should match features in the previous cases through some process ofsituation analysis. In this paper, we examine this problem in the legal domain, where lawyers know it asissue spotting. In particular, we present an implementation of issue spotting in CHASER, a legal reasoning system that works in the domain of tort law. This approach is a compromise between generality and efficiency, and is applicable to a range of problems and domains besides legal reasoning. In particular, it presents a principled way to use multiple cases for a single problem by exploiting the inherent structure present in many domains.
    Type of Medium: Electronic Resource
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  • 5
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 10 (1993), S. 311-339 
    ISSN: 0885-6125
    Keywords: Memory ; retrieval ; case-based reasoning ; similarity judgement
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Reasoning from prior cases or abstractions requires that a system identify relevant similarities between the current situation and objects represented in memory. Often, relevance depends upon abstract, thematic, costly-to-infer properties of the situation. Because of the cost of inference, a case-retrieval system needs to learn which descriptions are worth inferring, and how costly tht inference will be. This article outlines the properties that make an abstract thematic feature valuable to a case-based reasoner, and recasts the problem of case retrieval into a framework under which a system can explicitly and dynamically reason about the cost of acquiring features relative to their information value.
    Type of Medium: Electronic Resource
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  • 6
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 10 (1993), S. 249-278 
    ISSN: 0885-6125
    Keywords: General problem solving ; derivational analogy ; case-based reasoning ; search and retrieval costs ; replay ; learning by analogy
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Expertise consists of rapid selection and application of compiled experience. Robust reasoning, however, requires adaptation to new contingencies and intelligent modification of past experience. And novel or creative reasoning, by its real nature, necessitates general problem-solving abilities unconstrained by past behavior. This article presents a comprehensive computational model of analogical (case-based) reasoning that transitions smoothly between case replay, case adaptation, and general problem solving, exploiting and modifying past experience when available and resorting to general problem-solving methods when required. Learning occurs by accumulation of new cases, especially in situations that required extensive problem solving, and by tuning the indexing structure of the memory model to retrieve progressively more appropriate cases. The derivational replay mechanism is discussed in some detail, and extensive results of the first full implementation are presented. These results show up to a large performance improvement in a simple transportation domain for structurally similar problems, and smaller improvements when less strict similarity metrics are used for problems that share partial structure in a process-job planning domain and in an extended version of the strips robot domain.
    Type of Medium: Electronic Resource
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  • 7
    Electronic Resource
    Electronic Resource
    Springer
    Machine learning 10 (1993), S. 341-363 
    ISSN: 0885-6125
    Keywords: Heuristic search ; case-based reasoning ; learning ; A* algorithm
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract Case-Based Reasoning (CBR) is one of the emerging paradigms for designing intelligent systems. Preliminary studies indicate that the area is ripe for theoretical advances and innovative applications. Heuristic search is one of the most widely used techniques for obtaining optimal solutions to many real-world problems. We formulated the design of wastewater treatment systems as a heuristic search problem. In this article we identify some necessary properties of the heuristic search problems to be solved in the CBR paradigm. We designed a CBR system based on these observations and performed several experiments with the wastewater treatment problem. We compare the performance of the CBR system with the A* search algorithm.
    Type of Medium: Electronic Resource
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  • 8
    Electronic Resource
    Electronic Resource
    Springer
    Computational economics 3 (1990), S. 239-268 
    ISSN: 1572-9974
    Keywords: Knowledge-based systems ; approximate reasoning ; rule-based planning ; plausible reasoning ; case-based reasoning
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science , Economics
    Notes: Abstract Mergers and acquisitions (M&A) are currently revolutionizing the structure of corporate U.S.A. and annually involve deals totalling billions of dollars. Consequently, it is an area of intense activity and interest within the financial community. The process of planning an M&A is enormously complex and involves sophisticated reasoning and planning, by several parties such as the raider, the target company, investment banks, etc. Computer based tools are often invaluable for planning several stages of an M&A, such as generating forecasted cash flows. Current computer aids for M&A however do not provide adequate support for many essential features such as real time planning, reasoning under uncertainty, nonmonotonic inference, case-based reasoning, etc. MARS is a prototype M&A reasoning tool developed at General Electric Corporate R&D that attempts to provide such features in an integrated environment. MARS both simulates and provides advice regarding the complex reasoning and planning involved in an M&A deal. In doing so, it provides an excellent test bed architecture for the testing, development and integration of several ideas from artificial intelligence. MARS is implemented in COMMON LISP using RUM [15] on top of KEE [18]. RUM, a development environment for reasoning under uncertainty is based on Bonissone's theory of plausible reasoning [2–4] and was also developed at General Electric Corporate R&D.
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  • 9
    Electronic Resource
    Electronic Resource
    Springer
    Journal of intelligent information systems 2 (1993), S. 165-197 
    ISSN: 1573-7675
    Keywords: case-based reasoning ; compositional software reuse ; dataflow analysis ; program slicing program specification ; case base improvement ; inductive logic programming ; software testing
    Source: Springer Online Journal Archives 1860-2000
    Topics: Computer Science
    Notes: Abstract This software reuse system helps a user build programs by reusing modules stored in an existing library. The system, dubbed caesar (Case-basEd SoftwAre Reuse), is conceived in the case-based reasoning framework, where cases consist of program specifications and the corresponding C language code. The case base is initially seeded by decomposing relevant programs into functional slices using algorithms from dataflow analysis. caesar retrieves stored specifications from this base and specializes and/or generalizes them to match the user specification. Testing techniques are applied to the construct assembled by caesar through sequential composition to generate test data which exhibits the behavior of the code. For efficiency, inductive logic programming techniques are used to capture combinations of functions that frequently occur together in specifications. Such combinations may be stored as new functional slices.
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  • 10
    Electronic Resource
    Electronic Resource
    Springer
    Theory and decision 28 (1990), S. 203-242 
    ISSN: 1573-7187
    Keywords: Negotiation ; persuasive argumentation ; case-based reasoning ; multi-agent planning ; decision support ; agent modeling ; belief representation
    Source: Springer Online Journal Archives 1860-2000
    Topics: Sociology , Economics
    Notes: Abstract This paper presents Persuasive Argumentation as a means of guiding the negotiation process to a settlement. Decision theoretic approaches construct prescriptive models of the negotiation process that make various assumptions about the behavior of the negotiation participants but do not model changes in behavior. On the other hand, models for decision support leave the actual decisions to human negotiators, again not modeling or automating the negotiating process. In contrast to both approaches, our work deals with automating the negotiation process. This paper focuses on modeling the process by which the beliefs and behavior of negotiators are changed via persuasive argumentation. We claim that persuasive argumentation lies at the heart of negotiation and embodies the dynamics of negotiation. We present a model of persuasive argumentation that integrates Artificial Intelligence and decision theoretic methods. The model has been implemented as part of the PERSUADER, a multi-agent computer program that operates in the domain of labor negotiations.
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