Computational approaches to analogical reasoning

Hall, Rogers

doi:10.1016/0004-3702(89)90003-9

Cited by 186 publications

(77 citation statements)

References 27 publications

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“…Analogical reasoning provides a basic mechanism for effective connection between a reasoner's past and present experiences [23]. This notion is further extended; an AARS was proposed to allow unknown fuzzy rules to be deduced from an incomplete rule base in FIS modeling [17].…”

Section: Review Of the Approximate Analogical Reasoning Schema (Aars)mentioning

confidence: 99%

Enhancing a Fuzzy Failure Mode and Effect Analysis Methodology with an Analogical Reasoning Technique

Jee¹,

Tay²,

Ng³

2011

J. Adv. Comput. Intell. Intell. Inform.

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In this paper, a fuzzy Failure Mode and Effect Analysis (FMEA) methodology incorporating an analogical reasoning technique is presented. FMEA methodology was introduced as a formal and systematic procedure for evaluation of risk associated with potential failure modes in the 1960s. Bowles and Peláez [1] proposed a Fuzzy Inference System (FIS)-based Risk Priority Number (RPN) model as an alternative to the conventional RPN model. For an FIS-based RPN (a three-input FIS model), a large set of fuzzy rules are required, and it is tedious to collect the full set of rules. With the grid partition strategy, the number of fuzzy rules required increases in an exponential manner, and this phenomenon is known as the "curse of dimensionality" or the combinatorial rule explosion problem. Hence, a rule selection and similarity reasoning technique, i.e., Approximate Analogical Reasoning Schema (AARS) technique are implemented in a fuzzy FMEA in order to solve the problem. The experiment was conducted using a set of data collected from a semiconductor manufacturing line, i.e., underfill dispensing process, and promising results were obtained.

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Section: Review Of the Approximate Analogical Reasoning Schema (Aars)mentioning

confidence: 99%

Enhancing a Fuzzy Failure Mode and Effect Analysis Methodology with an Analogical Reasoning Technique

Jee¹,

Tay²,

Ng³

2011

J. Adv. Comput. Intell. Intell. Inform.

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“…Because we are interested by the earlier stages, we present these models only very briefly. Critical reviews and states of the art can be found, e.g., in 3 , 10 and 11 .…”

Section: Use Of Analogy Different Approachesmentioning

confidence: 99%

Two functions of analogical reasoning in design: a cognitive-psychology approach

Visser

1996

Design Studies

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To cite this version:Willemien Visser. Two functions of analogical reasoning in design. A cognitive-psychology approach. Design Studies, Elsevier, 1996, Design Cognition and Computation, 17 (4), pp.417-434. <10.1016/S0142-694X(96)00020-8>. Preprint of Visser, W. (1996). Two functions of analogical reasoning in design: A cognitive-psychology approach. Design Studies. Special Issue "Design Cognition and Computation",17, Abstract. On the basis of data collected in three empirical studies conducted on industrial designers, this paper identifies two different types of "spontaneous" use of analogy in design. Focus is on the first "stages" of analogical reasoning, i.e. construction of a target representation, and search and retrieval of a source. At the action-execution level, analogies are used in order to solve the current design problem; at the action-management level, in order to make the action-execution process cognitively more economical. Differences between the uses concern their dependence on the routine character of the task, the distance between target and source, and their link with creativity and reuse (or case-based reasoning). Two characteristics of our research make it rather original with respect to other cognitivepsychology research on analogical reasoning. First, the retrieval of analogues by the designers studied is "spontaneous": the analogous sources used by the designers are neither provided Preprint of Visser, W. (1996). Two functions of analogical reasoning in design: A cognitive-psychology approach. Design Studies. Special Issue "Design Cognition and Computation",17,[417][418][419][420][421][422][423][424][425][426][427][428][429][430][431][432][433][434] explicitly, nor cued. (In the analogical-reasoning vocabulary, a "source" is a problem/solution association related to a problem already solved, which constitutes the reference for the solution to the problem that is currently to be solved, the "target". The term "problem/solutions" or "problem/solution representations" was proposed in order to refer to both "problem/solution schemata" -i.e. representations of classes of problems and their solutions-and "particular problem/solution associations" -i.e. mental representations corresponding to specific problems and their solutions 1 .) In most research on analogical reasoning, the experimenters provide explicitly and/or cue the analogues to be exploited. Rare are the studies conducted on tasks in which the use of analogues would be helpful, but in which both this utility and the particular analogues themselves are not given, or at least suggested, to the subjects. Second, our studies have been conducted on use of analogy in a daily work context, whereas analogical reasoning has mostly been studied in artificially restricted tasks. Only very few data have been collected on the use of analogy in "real" tasks, e.g. in professional activities accomplished in their natural work context, or in learning in natural school or other educational environments. Data analysed in this paper ...

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“…However, they cannot be automatically adopted because there is no generally acceptable objective criterion for validating analogical inferences (Hall R. 1989, Maiden N. 1992). …”

Section: Revising Speci Cations On the Basis Of Analogiesmentioning

confidence: 99%

Analogical reuse of requirements specifications: A computational model

Spanoudakis¹

1996

Applied Artificial Intelligence

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Speci cations of requirements for new software systems can be revised, re ned or completed in reference to speci cations of requirements for existing similar systems. Although realized as a form of analogical problem solving, speci cation by reuse is not adequately supported by a vailable computational models for detecting analogies. This is chie y due to the following reasons: (1) It is assumed that speci cations are expressed according to the same speci cation model and in a uniform representation scheme. (2) Additional information is needed for the detection of analogies, which is not contained in the speci cations. (3) Performance scales poorly with the complexity of speci cations. This paper presents a computational model for detecting analogies, which addresses these issues to a certain extent. The application of the model in the speci cation of requirements by analogical reuse is demonstrated through an example, and its sensitivity to the representation of speci cations is discussed. Finally, the results of a preliminary empirical evaluation of the model are reported.

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Computational approaches to analogical reasoning

Cited by 186 publications

References 27 publications

Enhancing a Fuzzy Failure Mode and Effect Analysis Methodology with an Analogical Reasoning Technique

Enhancing a Fuzzy Failure Mode and Effect Analysis Methodology with an Analogical Reasoning Technique

Two functions of analogical reasoning in design: a cognitive-psychology approach

Analogical reuse of requirements specifications: A computational model

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