We present a model of similarity-based retrieval which attempts to capture three psychological phenomena: (1) people are extremely good at judging similarity and analogy when given items to compare. (2) Superficial remindings are much more frequent than structural remindings. (3) People sometimes experience and use purely structural analogical remindings. Our model, called MAC/FAC (for "many are called but few are chosen") consists of two stages. The first stage (MAC) uses a computationally cheap, non-structural matcher to filter candidates from a pool of memory items. That is, we redundantly encode structured representations as content vectors, whose dot product yields an estimate of how well the corresponding structural representations will match. The second stage (FAC) uses SME to compute a true structural match between the probe and output from the first stage. MAC/FAC has been fully implemented, and we show that it is capable of modeling patterns of access found in psychological ...

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this paper, we describe a framework for goal-driven learning and its relationship to prior and current theories from each of these perspectives.

In this paper, we describe CogSketch, an open-domain sketch understanding system built on the nuSketch architecture. CogSketch captures the multi-modal, unconstrained nature of sketching by focusing on reasoning over recognition. We describe this approach, as well as two application domains for CogSketch: cognitive modeling, and education.

. This paper explores some of the similarities and differences between cognitive models of analogy and case-based reasoning systems. I first point out a paradox in the treatment of adaptation in analogy and in case-based reasoning; a paradox which can be only resolved by expanding the role of adaptation in cognitive models of analogy. Some psychological research on the process of adaptation in human subjects is reported and then the implications of this research are propagated into analogy and then on into CBR. The argument is that some of the existing stages in CBR should be integrated into a more stream-lined architecture that would be more efficient than current schemes. 1. Introduction The present paper is part of a strong tradition of inter-communication between case-based reasoning (CBR) and psychologically-oriented work in cognitive science. My research roots are in cognitive psychology and the backdrop to my current case-based reasoning research is a broad, but unfinished, canv...

This is Appendix A to the thesis " Learning to See Analogies: a Connectionist Exploration."

Understanding how analogy is used in problem solving is an important problem in cognitive science. This paper describes a model of using worked solutions to solve new problems, in terms of structure-mapping processes in the Companions cognitive architecture. The Educational Testing Service independently evaluated the flexibility of the system by using AP Physics problems that were systematically varied to test different types of transfer. We also show that the model provides an explanation for many of the analogy events in VanLehn’s (1998) analysis of the use of analogy by students

The Incremental Analogy Machine (IAM) predicts that the order in which parts of an analogy are processed can affect the ease of analogical mapping. In this paper, the predictions of this model are tested in two experiments. Previous work has shown that such order effects can be found in attribute-mapping problems. In the first experiment, it is shown that these effects generalise to relational-mapping problems, when subjects' error performance (incorrect mappings) is considered. It is also found that relational-mapping problems are significantly harder than attribute-mapping problems. In the second experiment, it is shown using relational-mapping problems, that order effects can be demonstrated for doubles (two sentences about two indiviudals) in these problems. Throughout the paper it is shown that these results are best approximated by IAM's measure of the complexity of global mappings (the remaps-complexity measure), and not as has been found previously, by a measure using frequency...

The work of Johannes Kepler offers clear examples of conceptual change. In this article, using Kepler's work as a case study, we argue that analogical reasoning

v Declaration .................................... ix Acknowledgements................................ xi 1Prelude 1 TheVeryIdeaofRepresentation......................... 2 TypesofSimilarity ................................ 8 IsSimilarityIndeterminate? ........................... 11 TheRoleofSimilarityinCognition....................... 11 Summary&GeneralDiscussion......................... 14 2 Theories of Similarity 17 SimilarityDataSets................................ 17 SpatialRepresentation .............................. 21 FeaturalRepresentation.............................. 31 TreeRepresentation................................ 40 NetworkRepresentation ............................. 47 Alignment-BasedSimilarityModels....................... 48 TransformationalSimilarityModels ....................... 50 Summary&GeneralDiscussion......................... 54 i 3 On Representational Complexity 55 ApproachestoModelSelection ......................... 57 ChoosinganAdditiveClusteringRepresentation ................ 67 ChoosinganAdditiveTreeRepresentation ................... 82 ChoosingaSpatialRepresentation........................ 94 Summary&GeneralDiscussion......................... 95 4 Featural Representation 97 AMenagerieofFeaturalModels......................... 98 ClusteringModels.................................104 GeometricComplexityCriteria..........................106 AlgorithmsforFittingFeaturalModels .....................107 MonteCarloStudyI:DotheAlgorithmsWork? ................109 RepresentationsofKinshipTerms ........................117 MonteCarloStudyII:Complexity........................122 ExperimentI:Faces................................125 ExperimentII:Countries .............................1...