The purpose of my chapter is to give readers an appreciation
of the fact that a well-developed characteristic of our own behavior -
the ability to group different objects or stimuli together, to treat them
as though they were equivalent - is not unique to our species. This behavioral
characteristic, known variously as "categorization" or "conceptualization",
is easy to take for granted because for human adults, it is certainly second
nature. But the psychological processes responsible for this
remarkable ability may not be entirely obvious or may even be somewhat
different from what we might think. For instance, it is reasonable
to believe that human language provides the groundwork for categorization
given that we typically provide the same name for many things that we group
together (e.g., "fruit"). If language were truly necessary
for categorization, however, it would imply that animals without language
would be incapable of grouping together different objects they encounter
into the same class. But, as you will see, this implication is demonstrably
false. Consequently, other processes besides language must be involved
in categorization. Indeed, it may be that the common names given
to things we treat as equivalent are mostly a reflection of, rather than
just a foundation for, these processes.
The research literature contains many demonstrations of categorization
and conceptualization in non-human animals and a substantial proportion
of these involve pigeons and other avian species as experimental subjects
(see, for example, the chapters by Cook, (2001),
Huber (2001), Kirkpatrick
(2001), and Young & Wasserman,
(2001)). So, in the spirit of this cyberbook and my own particular research interests,
I will be focusing my discussion on the avian work.
There are two major points or "take-home" messages I hope to
convey. The first is that pigeons, like humans, readily group together things that
look alike. In other words, pigeons react similarly to objects that
perceptually resemble one another just as we react similarly to the coherent
groups that we call "cars", "people", "trees", etc. Of course, pigeons
(unlike humans) cannot supply a common language label to the members of
these groups, but they can be taught to do something very much analogous. Indeed, their version of "common names" is one way that we know that pigeons,
too, treat complex stimuli that are similar (but not identical) in appearance
as members of an equivalent class of objects. "Looking alike" or perceptual
similarity, then, is one basis for pigeon categorization, and it supports
the development of the pigeon version of common names. The issue
of what constitutes perceptual similarity is rather involved (see the chapters
by Blough
(2001) and by Huber (2001)), so I will skirt this issue and focus
instead on the behavioral consequences of providing the same name to things
that look alike.
Learning common names or responses to a set of stimuli is not merely
diagnostic of categorization. It is noteworthy for another reason:
those responses or names may themselves help to hold the group members
together more firmly (Catania, 1996). For example, our category "person"
may cohere even more strongly than the cohesion generated by perceptual
similarity alone precisely because we provide a common label for all objects
in that category. Similarly, the "person" category might be strengthened
because we've learned through experience that its members share the common
attribute of answering us when we speak to them.
This, then, brings me to my second, and perhaps more important,
point. The common associations shared by different objects promote the development
of an acquired equivalence between them. More specifically, pigeons
(like humans) group together objects on the basis of associative similarity,
and this occurs even when the objects do not look at all alike (i.e., are
perceptually dissimilar). A human example of this type of
categorization would be the class formed by cars, trains, airplanes, boats,
bicycles, and mopeds. Although very different in appearance, we recognize
all of these things as members of a group ("modes of transportation") bound
together by their common function of moving people from one place to another. Thus, common behavioral functions or associations are another basis for
categorization. Such acquired equivalence - what some psychologists
(e.g., Lea, 1984) refer to as "conceptualization" - is a major topic for
discussion in my chapter because it transcends mere "looks" and because
it, too, can be observed in pigeons' behavior.
After describing some techniques for revealing categorization and acquired
equivalence in pigeons and related species and the data that these techniques
have yielded, I will address how "bird brains" might manage such remarkable
behavioral feats. Here, I'll get into some psychological nitty-gritty
- namely, the theorizing about possible mechanisms that might produce acquired
equivalence effects in creatures without language. I'll end by describing
how these hypothesized mechanisms can be evaluated experimentally and
what actual experimental tests have revealed about them.
II. Categorization
by Appearance
One way that pigeons and humans categorize events is on the basis of
how similar they are in appearance to each other. In short, things
that look alike tend to be treated alike. The most straightforward
example of how perceptual similarity yields behavioral similarity is the
common name we typically assign to groups of objects, such as people, cars,
flowers, etc. We can, of course, perceptually differentiate between
group members (viz., we can tell one person from another). Nonetheless,
their common perceptual features are a major factor in our categorical
discrimination (Rosch, Mervis, Gray, Johnson, & Boyes-Braem, 1976),
and this ability produces tremendous economy in behavior (Younger &
Cohen, 1985). For example, we do not have to learn how to react individually
to each and every person but, instead, can generalize (quite appropriately)
the behavior we've learned across different individuals. Thus, we
know that speaking to one member of the group "people" - even someone we've
never previously encountered (and who is recognized as such) - will most
likely produce a reply in just the same way that we've actually experienced
in our interactions with other people. Conversely, we know that speaking
to members of the group "fish" will not produce the same effect.
This sort of discriminative behavior (i.e., generalization within a
group and discriminating between groups) and the generalization of this
behavior to new instances, has been elegantly documented and analyzed in
pigeons. Herrnstein and Loveland (1964), for example, trained pigeons
to peck for food at any of a number of photographic pictures that
contained a person or people somewhere in the picture. Figure
1 shows a series of "people" slides used in some of Herrnstein's
work. 
Just
as is typical in human experience, there was wide variation in the appearance
of the people shown in these slides - e.g., their number, orientation,
size, color of their clothing, etc. Other slides that did not contain
a person in them were also shown to the pigeons; when these appeared, pecking
at them did not produce food. Examples of "non-people" slides can also be
seen in
Figure 1.
With training, pigeons soon came to peck quickly and rapidly
at the "people" slides and
not to peck at the "non-people" slides. Moreover, this learned discriminative
behavior of pecking versus not-pecking at the various slides in the "people"
versus "non-people" categories, respectively. also generalized immediately
to pictures that the pigeons had never seen in training. In other
words, when shown a new slide containing a person, pigeons pecked at it,
despite never having been reinforced with food for pecking at that slide. Similarly, when shown a new slide without a person in it, the pigeons either
did not peck at it or did so much less frequently than to a "people" slide,
again despite never having experienced non-reinforcement with that particular
slide.
These latter results represent very crucial data for inferring categorization:
the pigeon's explicitly taught behavior generalized to new instances
of the "people" and "non-people" groups. In other words, they behaved
like we would if asked to say what type of object something was even though
we had never seen that particular object before. Our ability
to generalize the name/label we've learned for a group to novel instances/objects
is one of the litmus tests for categorization (Herrnstein, 1990; Keller
& Schoenfeld, 1950; Roberts, 1996).
An even closer analog to human categorization by appearance was developed
more recently by Wasserman and his colleagues (e.g. Bhatt, Wasserman,
Reynolds, & Knauss, 1988). Wasserman aptly refers to their task
as the pigeon version of the "name game", which parents often use to teach
their young children the names of different objects from a number of perceptually
distinct categories. On each training trial in the pigeon version
of the name game, hungry pigeons were shown a photographic slide on a center
viewing screen that depicted one of a variety of examples drawn from four
different categories: cats, chairs, cars, and flowers. After pecking at the slide appearing on the center screen, pigeons could
then obtain food by "naming/labeling" it appropriately. This 
meant pecking one of four different keys located at the vertices of the
viewing screen. Figure
2 shows the apparatus
used to display the pictures to the pigeons along
with the location of the different response options, and Figure
3
shows some of the slides used by Bhatt et al. (1988) in their studies. Thus, if a picture of a flower appeared on the center screen, pecking the
top left key produced food; if a picture of a car appeared, pecking the
top right key produced food; and so on.
Like the pigeons in Herrnstein and Loveland (1964) study, these pigeons
readily learned to correctly categorize the various pictures shown to them
in each training session. In this case, they quickly learned to confine
their pecks to one key when shown any instance of a cat, to another key
when shown any instance of a flower, and so on. The consistency in where
the pigeons pecked as a function of category (like the consistency in the
names we would provide) suggested that the pigeons had grouped the various
slides together by appearance. Things that looked alike were
treated alike, in other words. 
More importantly, the four different, explicitly taught pigeon "names"
(viz., location responses) generalized immediately and appropriately to novel
instances of each group that were later shown to them during a subsequent
generalization test (see Figure
4). I say "more importantly" because one might dismiss the data
obtained during initial training by claiming that the pigeons simply did
what they were taught, independently of any similarities (or dissimilarities)
each stimulus may have had to the other training stimuli. The generalization
test results obtained with the never-before-seen stimuli make that alternative
explanation less plausible.
Still, how confident can we be that these performances represent the
same sort of categorization-by-appearance that humans exhibit? For
instance, do pigeons really "see" perceptually coherent groups of objects,
as implied by the idea that perceptual similarity underlies their categorization
performances? These are difficult questions to answer definitively,
but other research (e.g., Astley & Wasserman, 1992; Cole & Honig,
1994) strongly suggests that the processes underlying the pigeons' performance
are indeed perceptually based. In other words, the consistency in
the pigeons' categorical responses is not merely an "accident" of learning
(and remembering) what response to make to each particular picture in order
to get food. To distinguish between "accident" and true categorization,
researchers have compared pigeons' performances on the task I've just described
with the performances of other pigeons that have been shown exactly the
same set of photographic slides but have been taught a "pseudo-category" task. In this task (Wasserman, Kiedinger, & Bhatt, 1988, Exp.
2), each picture is again associated with one of the four possible responses
but different pictures within a particular group (e.g., different cats
or different flowers) are associated with 
different
responses. For example, the pigeon might receive food for pecking the top left key
after seeing one of the flower pictures, but the bottom right key after
seeing a picture of a different flower, and so on. Pigeons
learn this task, too, but they do so much more slowly and they are not
as accurate in their choices as the "true category" pigeons as shown in Figure
5.
Other evidence that the pigeons' choices reflect the perceptual similarities
among the pictures in each class comes from Wasserman et al. (1988, Exp.
1) and from Astley and Wasserman (1992). In the Wasserman et al.
study, pigeons learned the four-choice task as depicted in Figure 3 but
with only two (instead of four) groups of stimuli - e.g., with only
flowers and cats. Pigeons had to respond to one location (e.g., the
top left key) to get food after seeing some of the flowers, but had to
respond to another location (e.g., the bottom right key) after seeing other
flowers. Similarly, different reinforced choices (e.g., top right
versus bottom left) were associated with different subgroups of cats. The pigeons were able to learn this task indicating that they could discriminate
between different flowers and between different cats. Of greater
interest were the types of errors the pigeons made when they misclassified
a slide. When pigeons pecked a wrong location following a particular
flower (or cat), the wrong location they pecked most often was the correct
location for the other subgroup of flowers (or cats). In other words,
pigeons were more likely to confuse the items within a category than the
items from different categories.
We can also ask whether the pigeons' ability to categorize different
objects in a group is something they've learned or is simply a reflection
of their biological/ perceptual apparatus. The answer to this
nature-nurture question is similar to those for many other nature-nurture
questions: Most likely, both. For instance, the category-pseudocategory
difference shows that the pigeon's visual system, too, perceives objects
that look alike and those that don't ("nature") and, as result, they can
be readily taught to respond in consistent ways on the basis of visual
appearance. However, the ability to transfer those responses to new
instances appears to depend on learning ("nurture") - in particular, on
learning to respond similarly to objects that are similar but not identical. In other words, pigeons (like humans) must learn that the inherent variation
among the features exhibited by group members is behaviorally unimportant
or inconsequential.
The contribution of the learning ("nurture") component can be gauged
by comparing how well pigeons transfer their responses to new exemplars
after having learned to categorize 1 instance from each group versus 12
instances (Wasserman & Bhatt, 1992). After training with
only 1 instance/group, pigeons do not respond correctly to new examples
(i.e., the accuracy of their choices is no better than chance). On
the other hand, they are very accurate after training with 12 pictures/group.
This latter finding is important for another reason to which I alluded
earlier. Specifically, even when it appears as though categorization/equivalence
is perceptually based (i.e., due to "nature"), chances are that the category
is also held together by the common behavior conditioned to the group members.
Common behavior is only possible, however, when pigeons and humans are
exposed to more than one member/group. But that situation is undoubtedly
the typical one. Thus, I would argue that these common associations
enhance the integrity of the group. Moreover, we know that common
associations per se will generate an acquired equivalence, even when
the members of the group do not look at all alike. It is that
phenomenon to which I now turn.
III. Categorization
by Association
Humans are adept at grouping together objects that have common functional
attributes. Examples of categories that fit this description (so-called
"superordinate" categories) include articles of clothing, modes of transportation,
and animals. Some authors (e.g., Lea, 1984) have argued that this form
of categorization is more in line with what we mean by the term "conceptualization"
because it carries with it the connotation that categorization often transcends
mere appearances. Are pigeons also capable of conceptualization,
despite the absence of language that could potentially provide mediators
to link such disparate objects together? They are indeed. Furthermore,
their abilities at categorization by association can be observed in a variety
of different learning situations.
Revealing this sort of grouping between objects sharing a common association
makes use of the transfer (or transfer-of-control) technique. The
rationale behind this technique is that new things learned specifically
about some members of a group should transfer without additional explicit
training to other members of the same group. Stated otherwise, if
a common association shared by different objects produces an acquired equivalence
between them, then those objects should also be interchangeable with one
another in new situations.
One example of categorization by association can be seen after differential
outcome training, a procedure described in the chapter by Grant and
Kelly (2001). Such training is often conducted in the context of delayed
matching-to-sample, so a brief description of a simple version of this
task is in order. On each trial of delayed matching, pigeons see
one of two different sample stimuli on the center key of a three-key display. After viewing and/or pecking the sample stimulus, two comparison or choice
stimuli appear simultaneously on the adjacent side keys. Pecking
one of the two simultaneously displayed comparisons is reinforced on trials
beginning with one sample, whereas pecking the other comparison is reinforced
on trials beginning with the other sample. An "incorrect" comparison
choice is never reinforced. Successive trials 
are separated from
one another by a blank period called the intertrial interval. An
animated illustration of "symbolic" delayed matching, in which the comparison
alternatives are different stimuli than the samples that precede them,
can be viewed by clicking here.
Note that in this animation,
the pigeon receives the same reinforcer - food - for pecking the vertical
comparison stimulus after the red sample and for pecking the horizontal
comparison stimulus after the green sample.
We can transform this procedure into a differential outcome task simply
by providing different reinforcers for the two correct comparison choices. For instance, if pigeons were both hungry and thirsty, they might receive
food for pecking the vertical comparison after the red sample and water
for pecking the horizontal comparison after the green sample (Brodigan
& Peterson, 1976). In other versions of differential outcome
training, different types of food are delivered for each correct choice
response (Edwards, Jagielo, Zentall, & Hogan, 1982) or food is delivered
with a higher probability for one response than for the other (Urcuioli, 1990). In some of my research (Urcuioli, 1990), hungry pigeons received
food in a lighted food hopper for making a correct choice response on one
trial type (e.g., red sample/vertical stripes) versus the lighted hopper
without food for making a correct response on the other trial type (e.g.,
green sample/horizontal stripes). The lighted hopper by itself serves
as a conditioned reinforcer, meaning that it is rewarding because of its
learned association with food. In any event, the lighted hopper is
a different outcome than when food accompanies it.
We might reasonably ask, then, whether the hue samples and the stripe
comparisons that "share" the same reward become equivalent. Unfortunately, the answer to this particular question is uncertain because
of complications arising from the fact that these stimuli appear in different
locations (i.e. the center key vs. the adjoining side keys). It turns
out that pigeons treat the same stimulus appearing in different locations
as if it were a different stimulus (Lionello & 
Urcuioli, 1998), so
devising a valid test for equivalence between samples and comparisons that
are associated with the same reinforcer is extraordinarily difficult. However, we can show that different center-key (sample) stimuli
associated with the same reward become equivalent (Edwards et al., 1982). Here's how this demonstration is accomplished (See Figure
6).
Initially, pigeons learn a red-sample/vertical-stripes and green-sample/horizontal-stripes
differential-outcome delayed matching task, as just described. Afterwards,
they learn two new associations that involve new stimuli appearing on the
center key (circle and dot) and the two familiar outcomes (food and lighted
hopper). For example, they might receive food shortly after seeing after
the circle on the center key but just the lighted hopper after seeing the dot. After this second phase of training, then, pigeons will have
been exposed to pairs of different center-key stimuli that have the same
reward association: namely, red and circle (both associated with food),
and green and dot (both associated with the lighted hopper only). We can now ask if those common reward associations have made the members
of each of these pairs equivalent. In other words, do the pigeons
treat the red and circle as if they belonged to one category, and likewise
green and dot?
If they do, then red and circle, and green and dot, should be interchangeable
with one another in novel situations. We can easily conduct a "novel-situation"
transfer test by returning to delayed matching but with the following
modification. Rather than presenting red and green as samples, present the circle and
dot instead. Then, when the vertical and horizontal stripes appear
on the side keys, observe which of these two comparisons the birds peck
following each "novel" sample. Note that although the vertical and
horizontal comparisons are familiar from initial training, they've never
before appeared after the circle and the dot. Nonetheless, assuming
that red and circle have become equivalent (and, likewise, green and dot), 
pigeons
should peck the vertical stripes after seeing the circle (because that
choice had been correct after red) and the horizontal stripes after seeing
the dot (because that choice had been correct after green). That's
precisely how pigeons behave, thus illustrating categorization by association. Figure
7 shows transfer results from two studies that used a design
like that depicted in Figure 6. Urcuioli (1990) actually used food
and a lighted hopper as the two outcomes for correct choice; Peterson (1984)
used food and the brief sounding of a tone. The blue bars show pigeons'
accuracy with the originally trained samples; the red bars show their accuracy
on the very first test session with the "novel" stimuli now appearing as
samples. With only two possible choices (i.e., between vertical and
horizontal comparisons), chance performance = 50% correct. Clearly,
birds in both of these studies were well above chance in their test performances
and, in Urcuioli (1990), chose as accurately with the "novel" samples as
with the explicitly trained ones.
The difference between this sort of test and the generalization tests
run in studies of categorization by appearance is that the stimuli
used to conduct the novel-situation test are not truly novel. The
circle and the dot center-key stimuli were previously seen by the pigeons,
but in a different context. The transfer test with these stimuli
simply assesses whether or not pigeons have learned "what's true of one
member of a group is true for all." In other words, the transfer
test essentially asks if prior learning to choose vertical after presentation
of one member of the "food" group (red), and horizontal after presentation
of one member of the "lighted hopper" group (green), generalizes to other
(familiar) members of these groups (i.e., circle and dot, respectively). Lea (1984) has called this "instance-to-category generalization" - the
behavior learned to one instance of a category generalizes to other instances
of that same category.
Another example of categorization by association in pigeons occurs after
training on a task called 
"many-to-one matching-to-sample". It is
similar to the matching task just described in that pigeons see center-key
(sample) stimuli presented individually on each trial followed by a pair
of choice or comparison alternatives on the adjacent side keys. In
the simplest many-to-one procedure, there are still two comparison alternatives
but four (rather than two) possible sample stimuli. Pecking
one comparison is reinforced after two of the sample stimuli, and pecking
the other comparison is reinforced after each of the remaining two samples. The common association in this task, then, is the correct comparison choice
shared by pairs of sample stimuli, as shown in the top panel of Figure
8.
Given the associative similarity between the red and circle samples
(i.e., both are cues to choose vertical) and between the green and the
dot samples (i.e., both are cues to choose horizontal), have pigeons learned
that the members of each sample pair are equivalent? We can again
answer this question by conducting a transfer test to see if what's true
of one instance of each category is true of all (viz., instance-to-category
generalization). For example, if we now explicitly teach pigeons
to make a new choice response to one member of each sample pair,
will that new response transfer to the other member of each pair?
To find out, we train pigeons (after their many-to-one experience) on
another delayed matching task involving two of
the original four sample
stimuli (e.g., red and green) and two new comparison choices (e.g., blue
and yellow). In this "reassignment" task, we might arrange for pigeons
to obtain food for pecking, say, blue after seeing the red sample and yellow
after seeing the green sample, as shown in the middle panel of Figure
8. (Click here for an interactive demonstration of
this experiment) After teaching the birds these new choices, we then ask if
pigeons will transfer these newly learned choices to the remaining (viz.,
the circle and dot) samples. Specifically, will pigeons now peck
blue after seeing the circle sample and yellow after seeing the dot sample
(bottom panel of Figure
8), even though they were never explicitly taught to do so? If so, this would be evidence of an acquired equivalence between the circle
and red, and between the dot and green, based upon the common comparison
associations shared by these samples during many-to-one training.
Actual tests of this nature have been conducted in a couple of different
ways. One has been reinforce whatever choice (blue or yellow)
the pigeon makes following each sample in the test phase (nondifferential
reinforcement). This way, how the pigeon performs over the course
of a test session is not biased in favor of certain sample-choice combinations. By using nondifferential reinforcement in testing, any preference that
pigeons do show 
for choosing blue after the circle sample and yellow after the dot sample
is strong evidence of an acquired sample equivalence that had developed
during initial, many-to-one training. Wasserman, DeVolder, and Coppage
(1992) have run this type of transfer test and found clear preferences
of just this sort. Some of their data appear in Figure
9.
Another test procedure run in my laboratory, provides differential
reinforcement in the test session: food is delivered only for
one particular choice after each sample (the alternative choice being
nonreinforced). For instance, pigeons might receive food for pecking blue (but not yellow)
after the circle sample and for pecking yellow (but not blue) comparison
after the dot sample. As just described, these reinforced choices
would be consistent with any acquired equivalence that may have
developed between the red and circle, and between the green and dot, samples
given that pigeons had already learned to peck blue after red and yellow
after green. Such "consistent" contingencies, then, should promote
very accurate performances in testing.
To avoid being misled about what that result, if obtained, would mean
- e.g., to avoid the possibility that "consistent" pigeons are accurate
in testing simply because they very quickly learn what goes with what within
the test session itself - another group of pigeons is tested with the opposite
contingencies: contingencies inconsistent with the choices
that should occur if the form and hue samples are equivalent. In
the inconsistent condition, pigeons would receive food for pecking yellow
(but not blue) after the circle sample and for pecking blue (but not yellow)
after the dot sample. In contrast to the consistent birds, they should
perform very poorly if the hues and forms are equivalent.
Actual data from a consistent versus inconsistent test assessment are
shown in Figure
10 which plots the percentage of the initial 16 transfer trials in which
individual birds in each condition chose the reinforced comparison. As
predicted on the basis of 
acquired equivalence, the consistent birds were generally very accurate,
matching well above the level expected by chance (50%) alone, whereas the
inconsistent birds were quite inaccurate, matching at or below the level 
expected
by chance. The substantial difference between conditions shows, without
a doubt, that the birds' choices in testing were not simply the result
of quickly learning new sample-choice relations. (If they were, the
average performances in these two test conditions should be identical.) Instead, the data provide solid evidence that pigeons categorize by
association. Pigeons had learned in many-to-one training, in other words, that the red
and circle samples were members of the same category as were the red and green
dot samples - categories formed on the basis of their common association with a particular
comparison choice.
These are not the only techniques for demonstrating categorization by
association (e.g., see Honey & Hall, 1989, and Kaiser, Sherburne, Steirn,
& Zentall, 1997) but they are common and have been used in similar
studies with humans (Spradlin, Cotter, & Baxley, 1973). An interesting
alternative assay, however, was recently described by Manabe, Kawashima,
and Staddon (1995) in a study with a different avian species - the budgerigar. They taught budgies to produce the comparison stimuli in matching-to-sample
by making one of two different vocal calls, a high or a low call, depending
on which sample stimulus (red or green) appeared on the center key. Pecking one of the two side-key comparisons (vertical or horizontal lines)
then produced food after one sample, whereas pecking the alternative comparison
produced food after the other sample. After the budgies had learned to
make the correct call to each sample and to peck the correct set of stripes
after each sample, Manabe et al. added two more samples to the procedure
(viz., vertical and horizontal stripes on the center key). This addition
created a many-to-one task: now, two different samples (one hue and
one line) shared the same reinforced choice response. The unique
twist to the Manabe et al. procedure was that the budgies could produce
the comparisons on trials with the new samples by making any
vocal call. (They were still required, however, to call high or low
to the hue samples.)
As training on the many-to-one task progressed, the budgies learned
which comparison to choose after each of the newly introduced line samples. But the more interesting
result was how they reacted to the new samples
themselves as learning about the correct choices proceeded. Specifically,
the budgies began to emit high and low calls to the vertical and horizontal
samples and, furthermore, these calls "matched" the calls they made
to the hue samples associated with the same comparison choice. In other words, if the budgies were required to make a high call to the
red sample, they began to make a high call to the line sample that was
associated with the same comparison choice as red. Likewise, if they
had to make a low call to the green sample, they began to make a low call
to the line sample that was associated with the same choice. Again,
this occurred despite the fact that any call made in the presence
of the line samples 
would produce the comparisons. An example of
a budgie making high and low calls to red and green samples and then matching
these samples to red and green comparisons is shown in the following video
clip. This clip does not correspond exactly to the delayed
matching procedure I've just described (viz., the comparisons are hues
instead of lines) but
it does clearly illustrate examples of the two different
calls that were explicitly conditioned to the hue samples and the matching
procedure in general. The choice and call data during many-to-one training for one subject
(S6) in Manabe et al.'s study appear in Figure
11. This figure shows the accuracy of correct comparison choice
on trials with the newly introduced samples over successive training sessions
and the proportion of calls to these samples that were consistent with
those made to the other (hue) samples with the same comparison association.
These fascinating and provocative results have another possible (and
plausible) interpretation (Saunders & Williams, 1998) which, unfortunately,
is too involved to explain here in a brief and simple fashion. Nonetheless,
the Manabe et al. (1995) results may yet represent another example
of categorization by association. Different-looking samples associated
with the same comparison ostensibly became members of the same group, and
that acquired equivalence became apparent in how the birds behaved to the
samples themselves. In other words, the behavior explicitly taught
to some samples - the high and low calls - transferred to the other samples
sharing the same comparison association. Assuming the acquired equivalence
interpretation to be correct, this effect would, once again, represent
instance-to-category generalization: what was true of one member
of each category (i.e., making a high or low call) became true of other
members of the same category (resulting in "matching" calls).
IV. Questions and Issues
There can be little doubt that pigeons are able to categorize different
things they see on the basis of similarity in appearance and similarity
in function. These capabilities show a higher level of functioning
than most people might normally attribute to them and, from the standpoint
of psychological research and theorizing, show that categorization and
acquired equivalence does not require human language. But the generalization
and transfer data that demonstrate the pigeon's categorization abilities
raise a few questions.
For example, if pigeons truly treat different objects as belonging to
the same category - either because of their appearance or their function
- then why are their performances during the generalization or
transfer tests not "perfect" or at least indistinguishable from their performances
with the training stimuli? One answer to this question is that
"equivalent" does not mean "equal/identical to". For instance, the
fact that pigeons can correctly sort new instances of flowers, chairs,
cats, etc. into different, previously learned response categories does
not mean that they are unable to distinguish between these new instances
and the ones used in training. In fact, the "subgroup" categorization
study (Wasserman et al.,1988, Exp. 1) discussed earlier shows that pigeons can
make those distinctions. This is important because if pigeons could
not discriminate between a new instance and a familiar one, then the
generalization test results from these studies would be trivial (viz.,
they would simply show that pigeons continue to do what they had been explicitly
taught to do with each given stimulus). A truly novel stimulus, then,
has some attribute(s) that is (are) detectably different from the stimuli
with which pigeons have been trained. Consequently, if the "particulars"
of the explicitly trained category members also influence the bird's behavior,
then new particulars would be expected to cause some disruption in performance,
thus yielding less than perfect test performance.
The same argument can be made for the transfer data from categorization-by-association
studies. An analogy to consider is that even though we treat shoes and
ties as belonging to a particular category (articles of clothing), we do
not treat them identically in all contexts and situations. Equivalent
implies treating these objects the same with respect to a particular function
(e.g., we wear them), but not necessarily with respect to all functions
(e.g., the part of the body on which we put them). Similarly, pigeons
that learn to choose vertical (as opposed to horizontal) after seeing either
a red or a circle sample might treat those samples as interchangeable (equivalent)
within that context. When later taught to choose a new (e.g., blue)
comparison after seeing just the red sample, they might learn (among other
things) that blue is what to peck after that particular stimulus. Consequently, when later shown the circle and asked to choose between blue
and yellow, they may not consistently choose blue because they recognize
that the circle is not red. Here, too, the particular physical properties
of each sample may exert some control over the birds' behavior, such that
a change in those properties should yield less-than-perfect transfer despite
acquired equivalence.
A second question might be: Is it truly the case that acquired
equivalence requires a common association in training? The answer
to that question is "yes". For example, in the differential outcome
paradigm, transfer of delayed matching across samples does not occur if
those samples do not share the same reward association (e.g., Peterson,
1984; Urcuioli 1990). Similarly, in the common comparison (many-to-one)
task, the transfer effects indicative of acquired equivalence do not materialize
if pigeons learn exactly the same set of sample-choice relations in training
but learn them in such a way that the common associations are never experienced
concurrently (Urcuioli, DeMarse, & Zentall, 1995).
This "non-concurrent" type of training can be seen in the bottom half
of Figure 12 in
the row 
designated
"One-to-many". The top half of Figure 12 shows
the concurrently trained common associations (in italics) that are part
of many-to-one delayed matching. [The entire top row writes out the
training contingencies and the transfer test that are depicted visually
in Figure 8.] Note especially that the two (initial and reassignment) training phases
for the One-to-many condition involve learning the same set of sample-choice
relationships as in the Many-to-one condition. Likewise, the transfer test
in both conditions is identical. More importantly, however, note that the samples associated with a common comparison stimulus (e.g.,
red and circle, and green and dot) appear in separate phases of training
in the One-to-many condition (italicized) - this is what I mean by
"non-concurrent". That seemingly minor difference has a major impact, however, on the
results of the transfer test used to assess acquired equivalence.
Specifically, the consistent versus inconsistent differences 
in test performances typically seen following many-to-one training are
absent following one-to-many training. This can be seen in the right
panel of Figure
13 which shows choice accuracies over the first 20 test trials for
consistently and inconsistently tested pigeons that had been exposed to
the one-to-many training procedure (Urcuioli et al., 1995, Exp. 2). Accuracies look very much alike in both test conditions. By contrast, the
left panel shows the corresponding data from birds initially trained on
many-to-one matching, the concurrently trained, common comparison association
task. A clear and substantial consistent-inconsistent difference
in transfer is once again obtained.
V. Psychological
Mechanism
It's one thing to show that training pigeons in certain ways yields
an acquired equivalence. It's another thing to explain how the transfer
indicative of equivalence comes about. What mechanism allows pigeons that
have been trained on many-to-one delayed matching to transfer the new choice
responses explicitly learned to one pair of samples to the other
pair?
This general issue was raised 60 years ago by the famous learning psychologist,
Clark Hull, in a paper entitled "The problem of stimulus equivalence
in behavior theory". In the introduction of that paper, Hull
quickly identified the problem discussed in this section: "How can
we account for the fact that a stimulus will sometimes evoke a reaction
to which it has never been conditioned?" (Hull, 1939, p. 9). If we
substitute "sample stimulus" in place of the word "stimulus" and "choice
response" in place of "a reaction", we have much the same question I posed
at the end of the preceding paragraph. Let's review the example of
transfer following many-to-one matching (top half of Figure
12) to see the issue.
Pigeons initially learn to match the red and circle samples to a vertical
choice and the green and dot samples to a horizontal choice. They
then learn to match one sample from each associative "set" to new comparisons:
the red sample to blue and the green sample to yellow. We then
find that pigeons can now match the circle sample to blue and the dot sample
to yellow, reactions that had never been conditioned. How do
they do it? Obviously, pigeons treated the red and circle samples
as equivalent and the green and dot samples, too. But what does "treating
them as equivalent" entail?
For instance, does it mean that the circle begins to look like red or
vice versa? This seems unlikely. Alternatively, do both the circle
and red samples remind the bird of the common choice (i.e., vertical) it
has to make after each of them to get food? Interestingly, something
very similar to this notion was Hull's explanation of equivalence effects. Were he to analyze the categorization-by-association effect, Hull would
argue that pigeons taught many-to-one matching to high levels of accuracy
anticipate which choice they will make when they see each sample stimulus. In other words, pigeons anticipate vertical upon seeing the red or the
circle sample and they anticipate horizontal upon seeing the green or dot sample.
The notion of anticipation is discussed and
illustrated
in Grant and Kelly (2001) and is popular for explaining differential
outcome and certain types of memory effects.
The diagram in
Figure14
shows how these hypothesized anticipatory reactions could produce 
transfer
of blue-yellow choices from one set of (explicitly trained) samples
to the other ("untrained") set. During reassignment training that
follows many-to-one matching and when pigeons learn to peck blue after
red and yellow after green, seeing the red sample generates the anticipatory
reaction of "vertical" (from the many-to-one task) and seeing the green
sample generates the anticipatory reaction of "horizontal". Consequently,
pigeons are also learning to choose blue when anticipating vertical and
to choose yellow when anticipating horizontal. The result, then,
is that birds should now be able to match any sample generating a "vertical"
or "horizontal" anticipation to blue and yellow. This means that
the circle and dot should be effective samples because they too remind
the birds of "vertical" and "horizontal", respectively. Hull called
this "secondary generalization"; others have termed it "mediated generalization":
blue-yellow choices generalize from samples to which they've been explicitly
conditioned (red and green) to samples to which they've not been
conditioned (circle and dot) because each pair of samples produces common
mediators (the anticipation of "vertical" and "horizontal").
Although this is a perfectly plausible explanation of categorization-by-association
in pigeons, is it accurate? One way to find out is to devise an independent
test of the mediated generalization hypothesis by, first, deriving a prediction
based on the assumption of anticipation and, second, running an experiment
to see if the prediction holds.
I have recently completed just such an
experiment. The entire
experiment involved three groups of pigeons, but only two need to be described. One group (Group First) was initially trained on many-to-one matching and
were then taught during subsequent reassignment training to make new choice
responses to one pair of samples. Finally, they were tested for acquired
equivalence using the remaining samples and the new choice responses. This
is the usual training and testing sequence I've previously described for
the many-to-one condition and that's illustrated in the top row of Figure
12. These pigeons, then, were expected to show the usual transfer
effects: accurate performances if tested with "consistent" contingencies,
but inaccurate performances if tested with "inconsistent" contingencies. Such findings would replicate my previous findings and, of course, would
be in line with the mediated generalization account.
The other group (Group Second) in this experiment was the more interesting
one. These pigeons learned the same two training tasks as Group First
(i.e., many-to-one matching and reassignment) but in reverse order. In other words, Group Second learned many-to-one matching after
they had already learned to match two of the samples to the comparisons
that would later appear in testing. Otherwise, what they learned
in the two phases of training and the contingencies (consistent or inconsistent)
to which they were exposed during the transfer test were exactly the same
as in Group First. [Imagine the order of initial and reassignment
training for the Many-to-one condition shown in Figure 12 being switched
- that's Group Second.]
According to the mediated generalization (anticipation) explanation,
Group Second should not show transfer indicative of acquired equivalence. In other words, their performances during the initial trials of the transfer
test should be close to chance (50%) and should not differ, on average,
as a function of whether the test involves consistent or inconsistent relations.
The reasoning behind these predictions is that what pigeons might learn
to anticipate upon seeing the samples in many-to-one matching (i.e., vertical
and horizontal) won't become connected to the other comparison stimuli
(blue and yellow) that appear in the other phase of training and, later, in the transfer
test. Why not? Because birds in Group Second
will have already learned to match with those other comparisons before
they learn any common anticipatory reactions to the samples in many-to-one
matching (and, thus, to the two samples originally matched to those other
comparisons).
The results from this experiment, however, did not support this
prediction. There was clear evidence of transfer (i.e., of acquired equivalence) in
Group Second as well as in Group First. Figure
15 shows some of the first-session transfer data. The blue
bars show choice accuracy over the first 20 transfer trials for birds tested
in the consistent condition; orange bars show choice accuracy for birds
tested in the inconsistent condition. The left and right panels plot
data from six birds each in Groups First and Second, respectively. For both groups, "consistent" pigeons (blue bars) matched well above the
level expected by chance, whereas "inconsistent" pigeons (orange bars)
matched at or below the level expected by chance.
What do these results mean? To me, they suggest that if
pigeons use a mediational strategy to guide their performances during transfer,
then the mediator - the common reaction that ties samples previously
associated with the same comparison choice together - can be something
other than the anticipation of those choices. In other words, even though
the comparison anticipation could serve as a mediator to produce the test results observed in Group
First, Group
Second's results indicate that pigeons probably have other means for grouping
together the commonly associated, many-to-one samples .
At this point, what those "other means" might be can only be
surmised. One possibility is that one sample serves as a reminder or a retrieval
cue for the other sample with which it shares a common association. For instance, given that the red and circle sample were both cues to choose
vertical, perhaps birds are reminded of red when they see the circle, and/or
vice versa. Researchers call this a "retrospective" process as opposed
to the anticipatory or "prospective" process already described, and distinction
that is nicely illustrated by animation
1 (retrospection) and animation
2 (prospection) from
Grant and Kelly (2000).
Figure
16 illustrates how such a retrospective process might work for Group
Second. Some of the pigeons in the consistent 
condition were required,
during their transfer test, to match the circle sample to blue and the
dot sample to yellow. If the circle sample reminded these birds of
"red" and the dot sample reminded them of "green" (i.e., of the hue samples
associated with the same comparisons as the circle and dot in many-to-one
matching), then this would closely correspond to what these pigeons actually
learned during initial training: choose blue after red and yellow after green. This correspondence is highlighted in Figure
16 by comparing the connections between blue and yellow and the colored
words. If being reminded of something ("red"and
"green")
is similar to the "real thing" (red and green),
then the consistent birds should be quite accurate during testing (and
the inconsistent birds quite inaccurate), as observed. This is, of
course, speculative although no more so that postulating anticipatory reactions.
VI. Conclusion
and Summary
Trying to pin down the psychological mechanisms responsible for these
and other findings in the categorization and acquired equivalence literature
represents some of the interesting and challenging questions in this line
of research. Whatever the mechanisms, however, they are clearly not
language-based and they permit a type of "cognitive" behavior that we so
readily take for granted in ourselves.
I should mention at this point, I suppose, that I am
not adopting
the position (nor are others in this line of work) that the extent of,
and the processes underlying, categorization and acquired equivalence are
no different in pigeons than they are in humans. To the contrary,
researchers are keenly aware of the fact that there are equivalence phenomena
readily exhibited by humans that have little, if any, known counterpart
in pigeons and other animals (e.g., Saunders, Williams, & Spradlin,
1996; Zentall, 1998). Perhaps down the road, this observed "gap"
in known conceptual abilities will shrink as we become better at refining
our techniques, and at developing new techniques, to study avian cognition. But even if
more discriminating research in the future fails to shrink
the gap, this will not detract at all from the significance of the demonstrable
abilities I have briefly reviewed in this chapter. After all, what we see in the pigeon's behavior may be a reflection of the origins of our
own, more extensive abilities, especially when we consider that we too
are largely the product of our experiences. The continued study of
avian cognition thus holds considerable promise in providing additional,
valuable insights into some of the basic behavioral processes of categorization,
acquired equivalence, and other cognitive phenomena.
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Preparation of this chapter and some of the research described in it were
supported by a research grant from the National Institutes of Mental Health
(MH56487) to Peter J. Urcuioli. The author thanks Will Vaughan, Jr. for
providing the slides used by Herrnstein in his visual categorization studies and, especially, Bob Cook whose extraordinary and unselfish efforts
brought this chapter and this book to fruition.
This chapter is dedicated to the memory of Werner K. Honig, the author's
mentor and one of the inspirational founders of the field of avian cognition.
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