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Our goal in this research is to collect a large
volume of time-evolving data from a system composed of human agents vying for
resources in a common environment, with the eventual aim of guiding the
development of computational models of human resource allocation. We have developed an experimental platform
that allows a large number of human participants to interact in real-time
within a common virtual world. Two
resource pools were created with different rates of replenishment. The participants’ task was to obtain as
many resource tokens as possible during an experiment. In addition to varying the relative
replenishment rate for the two resources (50-50, 65-35, 80-20), we manipulated
whether agents could see each other and the entire food distribution, or had
their vision restricted to food in their own location. As a collective, the agents would
optimally harvest the resources if they distribute themselves proportionally to
the distribution of resources.
Empirical violations of global optimality were found. First, there was a
systematic underutilization of the more preponderant resource. For example, agents distributed
themselves approximately 75% and 25% to resources pools that had relative
replenishment rates of 80% and 20%, respectively. The expected pay-off per agent was larger for pools with
relatively high replenishment rates.
Second, there were oscillations in the harvesting rates of the resources
across time, particularly when agents’ vision was restricted. Perceived underutilization of a
resource resulted in an influx of agents to that resource. This sudden influx, in turn, resulted
in a glut of agents, which then led to a trend for agents to depart from the
resource region. This cyclic activity
in the collective data was revealed by a Fourier analysis showing prominent
power in the range of about 50 seconds per cycle.
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This
is an abridged version of the Goldstone & Ashpole (in press).
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Four experiments
explored participants' understanding of the abstract principles governing
computer simulations of complex adaptive systems. Experiment 1 revealed
better transfer between computer simulations when they were governed by the
same abstract principle, even when the simulations' domains were
dissimilar. Experiments 2 and 3 showed better transfer of abstract
principles across simulations that were relatively dissimilar, and that this
effect was due to participants who performed relatively poorly on the initial
simulation. In Experiment 4, participants showed better abstract
understanding of a simulation when it was depicted with concrete rather than
idealized graphical elements. However, for poor performers, the idealized
version of the simulation transferred better to a new simulation governed by
the same abstraction. The results are interpreted in terms of competition
between abstract and concrete construals of the simulations. Individuals
prone toward concrete construals tend to overlook abstractions when concrete
properties or superficial similarities are salient.
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Concepts are
interrelated to the extent that the characterization each concept is influenced
by the other concepts, and isolated to the extent that the characterization of
one concept is independent of other concepts. The relative categorization accuracy of the prototype and
caricature of a concept can be used as a measure of concept interrelatedness. The prototype is the central tendency
of a concept, whereas a caricature deviates from the concept’s central tendency
in the direction opposite to the central tendency of other acquired
concepts. The prototype is
predicted to be relatively well categorized when a concept is relatively
independent of other concepts, but the caricature is predicted to be relatively
well categorized when a concept is highly related to other concepts. Support for these predictions comes
from manipulations of the labels given to simultaneously acquired concepts
(Experiment 1) and the order of categories during learning (Experiment 2).
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Five experiments
examined the nature of object representation. Participants made same-different
judgments between two multipart 3-D objects, according to rules where either
the object parts and their spatial relationship had to be considered
(role-relevant, RR) or just the object parts (role-irrelevant, RI). Results
indicate that it was easiest to judge two identical and orientationally aligned
objects according to either rule, followed by judging those that shared
identical parts located in different positions according to the RI rule. It was
most difficult to judge the latter according to the RR rule when they were
misaligned by rotation. These findings lend support to the hypothesis that
object representations at the image level, part level, or full structural
description level may be computed and used for making same-different
judgements. The implications of our findings for object recognition in general
and the role of spatial attention in particular are discussed.
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Scientists studying adult concept learning are typically careful to analyze the entire pattern of responses given across all of the trials of an experiment. Often times, the early trials are the most diagnostic because categorization accuracy quickly reaches an asymptote. We take some pride in tackling the hard problem of accounting for adaptive processes that account for category learning, unlike many psychophysicists, who simply throw out the first 1000 trials because steady-state performance has not yet been reached. However, lest we grow too smug, the chapters of this book provide a great service by reminding us that even though we analyze the very first trial of our experiment, we are still studying conceptual change that occurs almost imperceptibly close to the asymptote. By the time that our 20-year-old subjects come to our laboratories, they have learned the majority of the concepts that they will ever learn and virtually all of their truly foundational concepts. Relatively brief laboratory training suffices to teach students the rule “Circle Above Square” (Bruner, Goodnow, & Austin, 1956), a particular configuration of 9 dots (Posner & Keele, 1968), or a new fact such as that grebes are birds, but this rapid learning is only possible because it builds upon a longer and more profound process by which concepts such as Above (Quinn, this volume), Bird (Mervis, Pani & Pani, this volume), Animal (Mareschal, this volume; Mandler, this volume), and Animacy (Gelman & Koenig, this volume; Rakison, this volume) are learned.
Those of us who
want to develop theories of the learning and representation of adult concepts
cannot afford to remain blind to the conceptual development that makes possible
adult concept use. This life-long
learning provides us with the fundamental representations that we subsequently
combine and tweak. In assessing the
contribution of developmental research on concepts and categories to our
general understanding of human concepts, we will ask four questions: what are
concepts; what is the relation between perception and concepts; what are the
constraints on concept learning; and what are promising future directions for
research on concepts?
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Issues related to concepts and categorization are nearly ubiquitous in psychology because of peoples natural tendency to perceive a thing AS something. Zen meditation practices may or may not succeed in allowing a person to grasp the object itself rather than the labels and associations it evokes. In either case, the difficulty of this pursuit affirms the powerful impulse that we have to interpret our world. This act of interpretation, an act of seeing something as X rather than simply seeing it (Wittgenstein, 1953), is fundamentally an act of categorization.
The attraction
of research on concepts is that an extremely wide variety of cognitive acts can
be understood as categorizations. Identifying the person sitting across
from you at the breakfast table involves categorizing something as your
spouse. Diagnosing the cause of someones illness involves a disease
categorization. Interpreting a painting as a Picasso, an artifact as
Mayan, a geometry as Non-Euclidean, a fugue as baroque, a conversationalist as
charming, a wine as a Bordeaux, and a government as socialist are
categorizations at various levels of abstraction. The typically unspoken
assumption of research on concepts is that these cognitive acts have something
in common. That is, there are principles that explain many or all acts of
categorization. This assumption is controversial (see Medin, Lynch, &
Solomon, 2000), but is perhaps justified by its potential pay-off. If
there are common principles governing concepts in their diverse manifestations,
then discovering these principles would have a tremendous benefit, for we would
not only acquire an understanding of how people identify faces, recognize
letters, treat diseases, or form categories in a specialized domain. We
would also have a unified understanding of all of these phenomena as examples
of a generic process of concept formation.
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We explore one
aspect of meaning, the identification of matching concepts across systems (e.g.
people, theories, or cultures). We
present a computational algorithm called ABSURDIST (Aligning Between Systems
Using Relations Derived Inside Systems for Translation) that uses only
within-system similarity relations to find between-system translations. While illustrating the sufficiency of
within-system relations to account for translating between systems, simulations
of ABSURDIST also indicate synergistic interactions between intrinsic,
within-system information and extrinsic information.
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According to an
“external grounding” theory of meaning, a concept’s meaning depends on its
connection to the external world.
By a “conceptual web” account, a concept’s meaning depends on its
relations to other concepts within the same system. We explore one aspect of meaning, the identification of
matching concepts across systems (e.g. people, theories, or cultures). We present a computational algorithm
called ABSURDIST (Aligning Between Systems Using Relations Derived Inside
Systems for Translation) that uses only within-system similarity relations to
find between-system translations.
While illustrating the sufficiency of a conceptual web account for
translating between systems, simulations of ABSURDIST also indicate powerful
synergistic interactions between intrinsic, within-system information and
extrinsic information.
Applications of the algorithm to issues in object recognition, shape
analysis, automatic translation, human analogy and comparison making, pattern
matching, neural network interpretation, and statistical analysis are
described.
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The external
world must be filtered through our perceptual systems before it can have an
impact upon us. That is, the world we experience is formed by our
perceptual processing. However, it is not viciously circular to argue
that our perceptual systems are reciprocally formed by our experiences.
In fact, it is because our experiences are necessarily based on our perceptual
systems that these perceptual systems must be shaped so that our experiences
are appropriate and useful for dealing with our world
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Two experiments
examined how practice and time pressure influence holistic processing, defined
as the relative importance of feature interactions, in a face preference
task. Participants rated 32 cartoon
faces that varied along five dichotomous features (Experiment 1) or 27
realistic morphed faces that varied along three trichotomous dimensions
(Experiment 2), under high and low time pressure (operationalized as a short
versus long stimulus presentation time), over a series of experimental blocks.
In both experiments, the overall importance of facial features, but not of
feature interactions, increased over blocks and, in one condition of Experiment
1, under high versus low time pressure.
Analyses of idiosyncratic importance indicated that the feature effects
were due to the increasing importance of participants' idiosyncratically most
influential features. Functional
differences between face preferences and face recognition are offered to
explain and predict when facial features will be processed independently versus
holistically.
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Previous
research has shown that objects that are grouped together in the same category
become more similar to each other and that objects that are grouped in
different categories become increasingly dissimilar, as measured by similarity
ratings and psychophysical discriminations. These findings are consistent with
two theories of the influence of concept learning on similarity. By a strategic
judgment bias account, the categories associated with objects are explicitly
used as cues for determining similarity, and objects that are categorized
together are judged to be more similar because similarity is not only a
function of the objects themselves, but also the objectsí category labels. By a
representational change account, category learning alters the description of
the objects themselves, emphasizing properties that are relevant for
categorization. A new method for distinguishing between these accounts is
introduced which measures the difference between the similarity ratings of
categorized objects to a neutral object. The results indicate both strategic
biases based on category labels and genuine representational change, with the
strategic bias affecting mostly objects belonging to different categories and
the representational change affecting mostly objects belonging to the same
category.
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The reported experiments explore two
mechanisms by which object descriptions are flexibly adapted to support concept
learning: selective attention and dimension differentiation. Arbitrary
dimensions were created by blending photographs of faces in different
proportions, and mixing these blends together. Consistent with learned
selective attention, positive transfer was found when initial and final
categorizations shared either relevant or irrelevant dimensions, and negative
transfer was found when previously relevant dimensions became irrelevant.
Unexpectedly good transfer was observed when both irrelevant dimensions became
relevant and relevant dimensions became irrelevant, and was explained in terms
of participants learning to isolate one dimension from another. This account
was further supported by experiments indicating that conditions expected to
produce positive transfer via dimension differentiation produced better
transfer than conditions expected to produce positive transfer via selective
attention, but only when stimuli were composed of highly integral and
overlapping dimensions. We discuss the relation between dimension
differentiation and selective attention, mechanisms that may underlie these
processes, and implications for category learning research.
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Experiments explored whether spatially
neutral stimuli acquire the ability to automatically elicit spatial responses.
In Experiment 1, participants associated line-drawings with either left or
right key presses. Subsequently, the pictures were used in a Simon task wherein
participants made left and right key presses based on the color of the picture,
ignoring its shape. Participants responded more quickly when the key press
previously associated with the picture matched, rather than mismatched, the
response required by the picture's color. In Experiment 2, participants learned
response categories that grouped spatially ambiguous line-drawings together
with pictures of left- and right-pointing arrows and fingers. A subsequent
Simon task again yielded compatibility effects, indicating that the spatially
ambiguous pictures inherited the response biases of the other objects in their
category. Thus, responses directly associated with shapes, and indirectly associated
with shapes by category membership, are both automatically triggered even when
the responses are irrelevant and inappropriate.
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Five experiments
explored the question of whether new perceptual units can be developed if they
are diagnostic for a category learning task, and if so, what are the
constraints on this unitization process? During category learning, participants
were required to attend either a single component or a conjunction of five
components in order to correctly categorize an object. In Experiments 1-4, some
evidence for unitization was found in that the conjunctive task becomes much
easier with practice, and this improvement was not found for the single
component task, or for conjunctive tasks where the components cannot be unitized.
Influences of component order (Experiment 1), component contiguity (Experiment
2), component proximity (Experiment 3), and number of components (Experiment 4)
on practice effects were found. Using a Fourier Transformation method for
deconvolving response times (Experiment 5), prolonged practice effects yielded
responses that were faster than expected by analytic model that integrate
evidence from independently perceived components.
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Several models
of categorization assume that fixed perceptual representations are combined
together to determine categorizations. This research explores the
possibility that categorization experience alters, rather than simply uses,
descriptions of objects. Based on results from human experiments, a
model is presented in which a competitive learning network is first given
categorization training, and then is given a subsequent segmentation task,
using the same network weights. Category learning establishes detectors
for stimulus parts that are diagnostic, and these detectors, once established,
bias the interpretation of subsequent objects to be segmented.
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Confusions arise when 'stable' is equated with 'foundational.' Spurred on by the image of a house`s foundation, it is tempting to think that something provides effective support to the extent that it is rigid and stable. We will argue that when considering the role of perception in grounding our concepts, exactly the opposite is true. Our perceptual system supports our ability to acquire new concepts by being flexibly tuned to these concepts. Whereas the concepts that we learn are certainly influenced by our perceptual representations, we will argue that these perceptual representations are also influenced by the learned concepts. In keeping with one of the central themes of this book, behavioral adaptability is completely consistent with representationalism. In fact, the most straightforward account of our experimental results is that concept learning can produce changes in perceptual representations, the 'vocabulary' of perceptual features, that are used by subsequent tasks.
This chapter reviews theoretical
and empirical evidence that perceptual vocabularies used to describe visual
objects are flexibly adapted to the demands of their user. We will extend
arguments made elsewhere for adaptive perceptual representations (Goldstone,
Schyns, & Medin, in press; Schyns, Goldstone, & Thibaut, in press), and
discuss research from our laboratory illustrating specific interactions between
perceptual and conceptual learning. We will describe computer simulations that
provide accounts of these interactions using neural network models. These
models have detectors that become increasingly tuned to the set of perceptual
features that support concept learning. The bulk of the chapter will be
organized around mechanisms of human perceptual learning, and computer
simulations of these mechanisms.
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An ability to
assess similarity lies close to the core of cognition. In the time-honored
tradition of legitimizing fields of psychology by citing William James, `This
sense of Sameness is the very keel and backbone of our thinking` (James,
1890/1950; p. 459). Similarity plays an indispensable foundational role in
theories of cognition. People`s success in problem solving depends on the
similarity of previously solved problems to current problems. Categorization
depends on the similarity of objects to be categorized to category members.
Memory retrieval depends on the similarity of retrieval cues to stored
memories. Inductive reasoning is based on the principle that if an event is
similar to a previous event, then similar outcomes are predicted. An
understanding of these cognitive processes requires that we understand how
humans assess similarity. Four major psychological models of similarity are:
geometric, featural, alignment-based, and transformational.
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Perceptual
learning involves relatively long-lasting changes to an organism`s perceptual
system that improve its ability to respond to its environment. Four mechanisms
of perceptual learning are discussed: attention weighting, imprinting,
differentiation, and unitization. By attention weighting, perception becomes
adapted to tasks and environments by increasing the attention paid to important
dimensions and features. By imprinting, receptors are developed that are
specialized for stimuli or parts of a stimuli. By differentiation, stimuli that
were once indistinguishable become psychologically separated. By unitization,
tasks that originally required detection of several parts come to be
accomplished by detecting a single constructed unit representing a complex
configuration. Research from cognitive psychology, psychophysics, neuroscience,
expert/novice differences, development, computer science, and cross-cultural
differences is described that relates to these mechanisms. The locus, limits,
and applications of perceptual learning are also discussed.
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Human judgments
of similarity have traditionally been modelled by measuring the distance between
the compared items in a psychological space, or the overlap between the items`
featural representations. An alternative approach, inspired jointly by work in
analogical reasoning (D. Gentner, 1983; K. T. Holyoak & P. Thagard, 1989)
and interactive activation models of perception (J. L. McClelland & D. E.
Rumelhart, 1981), views the process of judging similarity as one of
establishing alignments between the parts of compared entities. A localist
connectionist model of similarity, SIAM, is described wherein units represent
correspondences between scene parts, and these units mutually and concurrently
influence each other according to their compatability. The model is primarily
applied to similarity rating tasks, but is also applied to other indirect measures
of similarity, to judgments of alignment between scene parts, to impressions of
comparison difficulty, and to patterns of perceptual sensitivity for matching
and mismatching features.
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Work in
philosophy and psychology has argued for a dissociation between
perceptually-based similarity and higher-level rules in conceptual thought.
Although such a dissociation may be justified at times, our goal is to
illustrate ways in which conceptual processing is grounded in perception, both
for perceptual similarity and abstract rules. We discuss the advantages, power,
and influences of perceptually-based representations. First, many of the
properties associated with amodal symbol systems (e.g. productivity and
generativity) can be achieved with perceptually-based systems as well. Second,
relatively raw perceptual representations are powerful because they can
implicitly represent properties in an analog fashion. Third, perception
naturally provides impressions of overall similarity, exactly the type of
similarity useful for establishing many common categories. Fourth, perceptual
similarity is not static but becomes tuned over time to conceptual demands.
Fifth, the original motivation or basis for sophisticated cognition is often
less sophisticated perceptual similarity. Sixth, perceptual simulation occurs
even in conceptual tasks that have no explicit perceptual demands. Parallels
between perceptual and conceptual processes suggest that many mechanisms typically
associated with abstract thought are also present in perception, and that
perceptual processes provide useful mechanisms that may be coopted by abstract
thought.
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This research
provides evidence for two competing attentional mechanisms. Attentional
persistence directs attention to attributes previously found to be predictive,
whereas contrast directs attention to stimuli that have not already been
associated with a category. Three experiments provide evidence for these
mechanisms. Experiments 1 and 2 revealed increased attention to an attribute
following training in which that attribute was relevant, providing evidence for
persistence. These experiments also revealed increased attention to an
attribute following training in which another, more salient attribute was
relevant, providing evidence for contrast. Experiment 3 used a subtractive method
to determine the contributions of persistence and contrast to changes in
attention to an attribute. The results suggest that persistence operates
primarily at the level of dimensions, whereas contrast operates at the level of
dimension values.
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According to an
influential approach to cognition, our perceptual systems provide us with a
repertoire of fixed features as input to higher-level cognitive processes. We
present a theory of category learning and representation in which features,
instead of being components of a fixed repertoire, are created under the
influence of higher-level cognitive processes. When new categories need to be learned,
fixed features face one of two problems: (1) High-level features that are
directly useful for categorization may not be flexible enough to represent all
relevant objects. (2) Low-level features consisting of unstructured fragments
(such as pixels) may not capture the regularities required for successful
categorization. We report evidence that feature creation occurs in category
learning and we describe the conditions that promote it. Feature creation can
adapt flexibly to changing environmental demands and may be the origin of fixed
feature repertoires. Implications for object categorization, conceptual
development, chunking, constructive induction and formal models of
dimensionality reduction are discussed.
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Similarity
comparisons are highly sensitive to judgment context. Three experiments explore
context effects that occur within a single comparison rather than across
several trials. Experiment 1 shows reliable intransitivities in which a target
is judged to be more similar to stimulus A than to stimulus B, more similar to
B than to stimulus C, and more similar to C than to A. Experiment 2 explores
the locus of Tversky`s (1977) diagnosticity effect in which the relative
similarity of two alternatives to a target is influenced by a third
alternative. Experiment 3 demonstrates reliable, though occasional, violations
of an assumption of monotonicity. The observed violations of common assumptions
to many models of similarity can be accomodated in terms of dynamic property
weighting processes based on specific forms of diagnosticity, and contrast sets
that are generated when a comparison is presented.
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In building models of cognition, it is customary to commence construction on the foundations laid by perception. Perception is presumed to provide us with an initial source of information that is operated upon by subsequent cognitive processes. And, as with the foundation of a house, a premium is placed on stability and solidity. Stable edifices require stable support structures. By this view, our cognitive processes are well behaved to the degree that they can depend upon the stable structures established by our perceptual system.
Considered collectively, the
contributions to this volume suggest an alternative metaphor for understanding
the relation between perception and cognition. The architectural equivalent of
perception may be a bridge rather than a foundation. The purpose of a bridge is
to provide support, but they do so by adapting to the supported vehicles.
Bridges, by design, sway under the weight of heavy vehicles, built on the
principle that it is better to bend than break. Bridges built with rigid
materials are often less resilient than their more flexible counterparts.
Similarly, the chapters collected here raise the possibility that perception
supports cognition by flexibly adapting to the requirements imposed by
cognitive tasks. Perception may not be stable, but its departures from
stability may facilitate rather than hamper its ability to support cognition.
Cognitive processes involved in categorization, comparison, object recognition,
and language may shift perception, but perception becomes better tuned to these
tasks as a result.
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Similarity
depends on representations of stimuli that are constructed and changed during
comparison-making. Specific features may be selectively weighted during
comparison, and the features used in a comparison may themselves be a product
of the comparison process. Traditional models of similarity and analogy rely on
representations that are assumed to exist prior to comparison and are
inflexible. Evidence from previous research indicates that weighting of
features in similarity judgments may vary dynamically during processing
(Goldstone, 1994; Goldstone & Medin, 1994). SIAM (Goldstone, 1994), a model
providing an account of dynamic weighting, is discussed. Additional studies
indicate that features may be developed or introduced during similarity
judgments. A methodology for examining process-oriented models that may account
for flexible representations is proposed.
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A continuum
between purely isolated and purely interrelated concepts is described. A
concept is interrelated to the extent that it is influenced by other concepts.
Methods for manipulating and identiying a concept`s degree of interrelatedness
are introduced. Relatively isolated concepts are empirically identified by a
relatively large use of nondiagnostic features, and by better categorization
performance for a concept`s prototype than for a caricature of the concept.
Relatively interrelated concepts are identified by minimal use of nondiagnostic
features, and by better categorization performance for a caricature than a
prototype. A concept is likely to be relatively isolated when: subjects are
instructed to create images for their concepts rather than find discriminating
features, concepts are given unrelated labels, and the categories that are
displayed alternate rarely between trials. The entire set of manipulations and
measurements supports a graded distinction between isolated and interrelated
concepts. The distinction is applied to current models of category learning,
and a connectionist framework for interpreting the empirical results is
presented.
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According to the
assumption of monotonicity in similarity judgments, adding a shared feature in
common to two items should increase or leave unchanged, but should never
decrease, their similarity. Violations of monotonicity are not predicted by
feature- or dimension-based models, but can be accommodated by alignment-based
models. According to alignment-based models, when structured displays are
compared, the parts of one compared display must be aligned, or placed in
correspondence with the parts of the other display. In two experiments,
evidence for nonmonotonicities is obtained that is generally, although not entirely,
consistent with the alignment-based model SIAM (Similarity as Interactive
Activation and Mapping; Goldstone, 1994). The primary assumption of the model
is that the calculation of similarity involves an interactive activation
process whereby correspondences between the parts of compared displays mutually
and concurrently influence each other. As SIAM predicts, the occurrence of
nonmonotonicities depends on the perceptual similarity of features and the
duration of presented comparisons.
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Categorical
perception is a phenomenon in which people are better able to distinguish
between stimuli along a physical continuum when the stimuli come from different
categories than when they come from the same category. In a laboratory
experiment with human subjects, we find evidence for categorical perception
along a novel dimension that is created by interpolating (i.e. morphing)
between two randomly selected bezier curves. A neural network qualitatively
models the empirical results with the following assumptions: 1) hidden
ÒdetectorÓ unit become specialized for particular stimulus regions with a
topologically structured competitive learning algorithm, 2) simultaneously,
associations between detectors and category units are learned, and 3) feedback
from the category units to the detectors causes the detectors to become
concentrated near category boundaries. The particular feedback used,
implemented in an ÒS.O.S. network,Ó operates by increasing the learning rate to
detectors that are neighbors to a detector that produces an improper
categorization.
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Most studies of the categorization of emotions tests the prototype model against the classical model, concluding that the prototype model offers the better explanation. Prototype models, as with all similarity-based models, posit that categorization depends on the similarity between the instance to be categorized and the category representation. However, we find that emotion similarity judgments and categorization judgments sometimes diverge. Specifically, information about changes in a person`s status and/or potency is weighted more heavily in categorization decisions than it is in similarity decisions. We argue that a knowledge-based model, rather than a similarity-based model, offers the best account of emotion categorization when information about status and potency changes is available.
The experiments
examined processes by which analyzing reasons may influence attitude judgments.
Participants made multiple liking judgments on sets of stimuli that varied
along six a priori dimensions. In Study 1, the stimulus set consisted of 64
cartoon faces with six binary-valued attributes (e.g. a straight versus crooked
nose). In Study 2, the stimuli were 60 digitized photographs from a college
yearbook that varied along six dimensions uncovered through multi-dimensional
scaling. In each experiment, half of the participants were instructed to think
about the reasons why they liked each face before making their liking rating.
Participants` multiple liking ratings were then regressed on the dimension
values to determine how they weighted each dimension in their liking judgments.
Results support a process whereby reasoning leads to increased variability and
inconsistency in the weighting of stimulus information. Results are discussed
with respect to Wilson`s model of the disruptive effects of reasoning on
attitude judgments (e.g. Wilson, Dunn, Kraft, & Lisle, 1989).
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Subjects were shown
simple objects and were asked to reproduce the colors of the objects. Even
though the objects remained on the screen while the subjects reproduced the
colors and the objects` shapes were irrelevant to the subjects` task, subjects`
color perceptions were influenced by the shape category of an object. For
example, objects that belonged to categories with redder objects were judged to
be more red than identically colored objects belonging to another category.
Further experiments showed thatX the object categories that subjects use,
rather than being fixed, depend on the objects to which subjects are exposed.
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In the first
part of this article, empirical evidence is reviewed that suggests a
substantial amount of flexibility and context-sensitivity in peopleUs judgments
of similarity. Four examples of flexible similarity from our laboratory are
considered in detail. In the second part of the article, evidence for
relatively constrained, invariant similarity assessments is considered. In the
final section, a resolution to these apparently contradictory views on
similarity is proposed. Assessments of similarity are used to make inferences
from one entity to another. In some situations, flexible similarity is needed
to tailor inferences to oneUs knowledge of the entities and their relations. In
other situations, particularly those in which specific knowledge is missing or
unavailable, a relatively constant similarity is needed to establish generally
permissible inferences. Thus, the flexibility and stability of similarity may
reflect its different cognitive uses.
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Research and
theory in decision making and in similarity judgment have developed along
parallel paths. We review and analyze phenomena in both domains that suggest
that similarity processing and decision making share important correspondences.
The parallels are explored at the level of empirical generalizations and
underlying processing principles. Important component processes that are shared
by similarity judgments and decision making include generation of alternatives,
recruitment of reference points, dynamic weighting of aspects, creation of new
descriptors, development of correspondences between items, and justification of
judgement.
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Four experiments
investigated the influence of categorization training on perceptual
discriminations. Ss were trained according to 1 of 4 different categorization
regimes. Subsequent to category learning, Ss performed a Same-Different
judgement task. Ss` sensitivities (d`s)
for discriminating between items that varied on a category(ir)relevant
dimensions were measured. Evidence for acquired distinctiveness (increased
perceptual sensitivity for items that are categorized differently) was
obtained. One case of acquired equivalence (decreased perceptual sensitivity
for items that are categorized together) was found for separable, but not
integral, dimensions. Acquired equivalence within a categorization-relevant
dimension was never found for either integral or separable dimensions. The
relevance of the results for theories of perceptual learning, dimensional
attention, categorical perception, and categorization are discussed.
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The relation
between similarity and categorization has recently come under scrutiny from
several sectors. The issue provides an important inroad to questions about the
contributions of high-level thought and lower-level perception in the
development of people`s concepts. Many psychological models base categorization
on similarity, assuming that thing belong in the same category because of their
similarity. Empirical and in-principle arguments have recently raied objections
to this connection, on the grounds that similarity is too unconstrained to
provide an explanation of categorization, and similarity is not sufficiently
sophisticated to ground most categories. Although these objections have merit, a
reassesment of evidence indicates that similarity can be sufficiently
constrained and sophisticated to provide at least a partial account of many
categories. Principles are discussed for incorporating similarity into theories
of category formation.
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The question of
"what makes things seem similar?" is important both for the pivotal
role of similarity in theories of cognition and for an intrinsic interest in
how people make comparisons. Similarity frequently involves more than listing
the features of the things to be compared and comparing the lists for overlap.
Often, the parts of one thing must be aligned or placed in correspondence with
the parts of the other. The quantitative model with the best overall fit to
human data assumes an interactive activation process whereby correspondences
between the parts of compared things mutually and concurrently influence each
other. An essential aspect of this model is that matching and mismatching
features influence similarity more if they belong to parts that are placed in
correspondence. In turn, parts are placed in correspondence if they have many
features in common and if they are consistent with other developing
correspondences.
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Measurements of
similarity have typically been obtained through the use of rating, sorting, and
perceptual confusion tasks. In the present paper, a new method of measuring
similarity is described, in which subjects rearrange items so that their
proximity on a computer screen is proportional to their similarity. This method
provides very efficient data collection. If a display has n objects, then, after subjects have rearranged the
objects (requiring slightly more than n movements), n(n-1)/2 pairwise similarityes can be recorded. As long
as the constraints imposed by two-diminsional space are not too different from
those intrinsic to psychological similarity, the technique apears to offer an
efficient, user-friendly, and intuitive process for measuring psychological
similarity.
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Similarity as
interactive activation and mapping (SIAM), a model of the dynamic course of
similarity comparisons, is presented. According to SIAM, when structured scenes
are compared, the parts of one scene must be aligned, or placed in
correspondence, with the parts from the other scene. Emerging correspondences
influence each other in a manner such that, with sufficient time, the strongest
correspondences are those that are globally consistent with other
correspondences. Relative to globally inconsistent feature matches, globally
consistent feature matches influence similarity more when greater amounts of
time are given for a comparison. A common underlying process model of scene
alignment accounts for commonalities between different task conditions.
Differences between task conditions are accounted for by principled parametric
variation within the model.
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The organization
of this chapter is as follows. First, we review the role of mapping and global
consistency in both low-level visual perception and abstract analogy and then
suggest that mapping and consistency also apply to similarity assessment. Next,
we review current models of similarity and note that they have little to say
about processes by which corresponding properties are aligned. We then describe
some experiments on alignment processes associated with comparisons. We account
for these results with an interactive activation model of alignment and contrast
this model with a number of alternative.s Finally, we asses the role of mapping
or alignment in comparisons more generally and offer some conclusions.
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One productive and influential approach to cognition maintains that categorization, object recognition, and higher-level cognitive processes operate on the output of lower-level perceptual processing.That is, our perceptual systems provide us with a set of fixed features. These features are the inputs to higher-level cognitive processes.
Recently, researchers in psychology, computer science, and philosophy have questioned this unidirectional approach, arguing that in many situations, the high-level cognitive process being executed has an influence on the lower-level features that are created. For example, in addition to categorization being based on featural descriptions of objects, it might also be the case that the categorization process partially creates the featural decriptions that are used. Rather than viewing the "vocabulary" of primitives to be fixed by low-level processes, this view maintains that the vocabulary is dependent on the higher-level process that uses the vocabulary. This symposium will investigate several issues related to bidirectional interactions between high-level and low-level cognitive processes.
o Medin, Douglas L. The Pervasiveness of Constructive Processes
o Thibaut, Jean-Pierre. Role of Variation and Knowledge on Stimuli Segmentation: Developmental Aspects
o Mozer, Michael. Computational Approaches to Functional Feature Learning
o French, Robert. Representation-building in Analogical Reasoning
o
Schyns, Philippe G. A Functional Approach to Feature
Learning
We present the results of a simple experiment in lower-case letter recognition. Unlike most psychology studies of letter recognition, we include in our data set letters at the extremes of their categories and investigate the recognition of letters of multiple typefaces. We are interested in the relationship between the recognition of normal letters and the recognition of non-standard letters. Results provide empirical evidence for top-down conceptual constrains on letter perception in the form of roles and relations between perceptually-based stuctural subcomponents. A process model based on the hypothesis developed below is currently being implemented.
Several models of categorization suggest that fixed inputs (features) are combined together to create categorization rules. It is also possible that categorization influences what features are perceived and used. This experiment explored the possibility that categorization training influences how an object is decomposed into parts. In the first part of this experiment, subjects learned to categorize objects based on particular sets of line segments. Following categorization training, subjects were tested in a whole-part decomposition task, making speeded judgements of "does whole X contain probe Y." All diagnostic and nondiagnostic category parts were used as parts within the whole objects, and as probes. Categorization training in the first part of the experiment affected performance on the second task. In particular, subjects were faster to respond when the whole object contained a part that was diagnostic for categorization than when it contained a nondiagnostic part. When the probe was a diagnostic category part subjects were faster to respond that it was present than absent, and when the probe was a nondiagnostic part, subjects were faster to respond that it was absent than that it was present. These results are discussed in terms of perceptual sensitivity, response bias, and the modulating influence of experience.
Perceptual
equivalents of confirmation biases and framing effects are observed in
subjects` estimates of feature numerosity. Subjects are asked to estimate the percentage
of display items that have a particular feature. Features either are randomly
distributed or are spatially clustered such that features of the same type tend
to be close. Subjects systematically overestimate the prevalence of features in
clustered displays. The pattern of results is best explained by a reional
salience bias: Features tend to be more salient if they belong to regions that
have a high concentration of instruction-mentioned features. The regional
salience bias is contrasted with a feature salience bias: Features tend to be
more salient if they are mentioned in the instructions. The relations among the
observed perceptual bias and traditional confirmation biases, numeric
estimation, and attention are discussed.
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Previous research (Goldstone, 1991) has suggested that concepts differ in their degree of dependency on other concepts. While some concepts` characterizations depend on other simultaneously acquired concepts, other concepts are relatively isolated. The current experiments provide a new measure of a concept`s interrelatedness/isolation. It is assumed that if the prototype of a concept is classified with greater accuracy than a caricature, then the concept is relatively independent of the influences of other concepts. If a caricature is more easily categorized than the prototype, then the concept is relatively dependent on other concepts. If these assumptions are made, then the current experiments provide converging support for a interrelated/isolated distinction. Instructing subjects to form images of the concepts to be acquired, or infrequently alternating categories during presentation, yields relatively isolated concepts. Instructing subjects to try to discriminate between concepts, or frequently alternative categories, yields relatively interrelated concepts.
This study involved noninvasive observation of copy-machine use at a university institution. Patrons` self-reports of copies were compared to the actual number of copies made. Results indicate a systematic underreporting of actual copies. Intermediate-level dishonesty is common place, whereby patrons underestimate the number of copies made but refrain from profit-maximizing dishonesty even in the absence of an external monitor. The percentage of copies unreported is approximately constant over different copy job sizes. There are strong self-imposed constraints on the level of allowed dishonesty. However, there is an increased tendency for intermediate-level dishonesty as copy job size increases. Nonreporting of copies and correct reporting of copies are both common for small jobs. There is an empirical dissociation between the prevalence and the degree of dishonest behaviors, interpretable in terms of different motivations that arise when financial gains are high and low. The results are also diagnostic in assessing the nature of the tradeoff between the competing motivations to maximize financial profits and to behave honestly.
This article
reviews the status of similarity as an explanatory construct with a focus on
similarity judgements. For similarity to be a useful construct, one must be
able to specify the ways or respects in which two things are similar. One
solution to this problem is to restruct the notion of similarity to hard-wired
perceptual processes. It is argued that this view is too narrow and limiting.
Instead, it is proposed that an important source of constraints derives from
the similarity comparison process itself. Both new experiments and other
evidence are described that support the idea that respects are determined by
processes internal to comparisons.
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We previously introduced an exemplar model, named GCM-ISW, that exploits a highly flexible weighting scheme. Or simulations showed that it records faster learning rates and higher asymptotic accuracies on several artificial categorization tasks than models with more limited abilities to warp input spaces. This paper extends our previous work; it describes experimental results that suggest human subjects also invoke such highly flexible schemes. In particular, our model provides significantly better fits than models with less flexibility, and we hypothesize that humans selectively weight attributes depending on an item`s location in the input space.
Two methods of representing concepts are distinguished and empirically investigated. Negatively defined concepts are defined in terms of other concepts at the same level of abstraction. Positively defined concepts do not make recourse to other concepts at the same level of abstraction for their definition. In two experiments, subjects are biased to represent concepts underlying visual patterns in a positive manner by instructing subjects to form an image of the learned concepts and by initially training subjects on minimally distorted concept instances. Positively defined concepts are characterized by a large use of nondiagnostic features in concept representations, relative to negatively defined concepts. The distinction between positively and negatively defined concepts can account for the dual nature of natural concepts - as directly accessed during the recognition of items, and is intricately interconnected to other concepts.
Four experiments
examined the hypothesis that simple attributional features and relational
features operate differently in the determination of similarity judgements.
Forced choice similarity judgments ("Is X or Y more similar to Z?")
and similarity rating tasks demonstrate that making the same featural change in
two geometric stimuli unequally affects their judged similarity to a third
stimulus (the comparison stimulus). More specifically, a featural change that
causes stimuli to be more superficially similar and less relationally similar
increases judged similarity if it occurs in stimuli that already share many
superficial attributes, and decreases similarity if it occurs in stimuli that
do not share as many superficial attributes. These results argue against an
assumption of feature independence which asserts that the degree to which a
feature shared by two objects affects similarity is independent of the other
features shared by the objects. The MAX hypothesis is introduced, in which
attributional and relational similarities are separately pooled, and shared
features affect similarity more if the pool they are in is already relatively
large. The results support claims that relations and attributes are
psychologically distinct and that formal measures of similarity should not
treat all types of matching features equally.
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There has been an upsurge of interest, in both artificial intelligence and cognitive psychology, in exemplar-based process models of categorization, which preserve specific instances instead of maintaining abstractions derived from them. Recent exemplar-based models provided accurate fits for subject results in a variety of experiments because, in accordance with Shepard`s (1987) observations, they define similarity to degrade exponentially with the distance between instances in psychological space. Although several researchers have shown that an attribute`s relevance in similarity calculations varies according to its context (i.e., the values of the other attributes in the instance and the target concept," previous exemplar models define attribute relevance to be invariant across all instances. This paper introduces the GCM-ISW model, an extension of Nosofsky`s GCM model that uses context-specific attribute weights for categorization tasks. Since several researchers have reported that humans make context-sensitive classification decision, our model will fit subject data more accurately when attribute relevance is context-sensitive. We also introduce a process component for GCM-ISW and show that its learning rate is significantly faster than the rates of both previous exemplar-based process models when attribute relevance varies among instances. GCM-ISM is both computationally more efficient and more psychologically plausible than previous exemplar-based models.
Conventional
wisdom and previous research suggest that similarity judgements and difference
judgements are inverses of one another. An exception to this rule arises when
both relational similarity and attributional similarity are considered. When
presented with choices that are relationally or attributionally similar to a
standard, human subjects tend to pick the relationally similar choice as more
similar to the standard and as more
different from the standard. These results not only reinforce the general
distinction between attributes and relations but also show that attributes and
relations are dynamically distinct in the processes that give rise to
similarity and difference judgments.
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Last updated June 17, 2003. Please send comments or corrections to rgoldsto@indiana.edu