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Computing and Philosophy pp 207–225Cite as

Internal Supervision & Clustering: A New Lesson from ‘Old’ Findings?

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Part of the book series: Synthese Library ((SYLI,volume 375))

Abstract

Learning is most often treated as a psychologically rich process in the extant literature. In turn, this has a number of negative implications for clustering in machine learning (i.e. grouping a set of objects so that objects in the same group – cluster – resemble each other more than they resemble members of other groups) to the extent that psychologically rich processes are in principle harder to model. In this paper, I question the view of learning as psychologically rich and argue that mechanisms dedicated to perception and storage of information could also be used in categorization tasks. More specifically, I identify the minimum resources required for learning in the human mind, and argue that learning is greatly facilitated by top-down effects in perception. Modeling the processes responsible for these top-down effects would make modeling tasks like clustering simpler as well as more effective. For clustering is seen here as building upon associations between perceptual features, while connection weightings and top-down effects substitute external supervision in executing the function of error identification and rewards.

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Notes

  1. 1.

    See for example Seymour & Minsky’s critique of genetic programming (e.g. 1988) or Dreyfus stance on the uncomputability of common sense (e.g. 1965, 1967, 1972). I owe this suggestion to Mario Verdicchio.

  2. 2.

    What is not clear, at least in Barsalou’s (1999) paper is whether frames represent information/representations of a particular instance that is used to represent the category as a whole, essentially in the sense that Hume (1739/1978), Berkeley (1710/1957) and more recently Prinz (2002) argue for or whether the process of building a frame stands for a Lockean (1690/1975) process of abstraction. See Barsalou (2005) and Tillas (forthcoming) for a detailed discussion of related issues.

  3. 3.

    Think of ‘locus’ in terms of Perry’s (2001) ‘mental files’ metaphor.

  4. 4.

    See Barsalou (2005) for a detailed discussion of perceptually orientated view of abstraction.

  5. 5.

    This claim enjoys significant empirical support, amongst others, by Spivey and Geng (2001), Chao et al. (1999), Barsalou (1999), Demarais and Cohen (1998), Farah (1995, 1989), Finke (1989), Kosslyn et al. (1995), Brandt and Stark (1997), and Norton and Stark (1971).

  6. 6.

    Despite appealing to a connectionist model to illustrate my point, I am not committed to connectionism.

  7. 7.

    A clear-cut case of evidence showing that stored representations influence perception via driving selective attention comes from Gestalt psychology and optical illusions and more specifically from the process of a gestalt-shift or the point where an observer identifies a different image while looking at the same display.

  8. 8.

    For studies of frequency potentiation (LTP), which greatly resembles Hebbian learning, see Lomo (1966), Bliss and Lomo (1973), Bliss and Gardner-Medwin (1973), Martinez et al. (2002). For objections to the claim that LTP is a learning mechanism see Shors and Matzel (1997). For a reply to Shors and Matzel see amongst others Hawkins (1997).

  9. 9.

    E.g. Barsalou (1999), Findlay and Gilchrist (2003), Gazzaniga et al. (1998), Biederman (1987), Hochberg (1999), Goldstone (1994), and Smith and Heise (1992).

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Acknowledgements

I am grateful to Patrice Soom and James Trafford for their helpful comments on earlier drafts of this chapter.

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  1. Department of Philosophy, University of Düsseldorf, Düsseldorf, Germany

    Alexandros Tillas

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Correspondence to Alexandros Tillas .

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  1. Anatolia College/ACT, Thessaloniki, Greece

    Vincent C. Müller

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Tillas, A. (2016). Internal Supervision & Clustering: A New Lesson from ‘Old’ Findings?. In: Müller, V.C. (eds) Computing and Philosophy. Synthese Library, vol 375. Springer, Cham. https://doi.org/10.1007/978-3-319-23291-1_14

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