To save this undefined to your undefined account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you used this feature, you will be asked to authorise Cambridge Core to connect with your undefined account.
Find out more about saving content to .
To save this article to your Kindle, first ensure email@example.com is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below.
Find out more about saving to your Kindle.
Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
According to the dominant computational approach in cognitive
science, cognitive agents are digital computers; according to the
alternative approach, they are dynamical systems. This target article
attempts to articulate and support the dynamical hypothesis. The
dynamical hypothesis has two major components: the nature hypothesis
(cognitive agents are dynamical systems) and the knowledge
hypothesis (cognitive agents can be understood dynamically). A wide
range of objections to this hypothesis can be rebutted. The conclusion
is that cognitive systems may well be dynamical systems, and only
sustained empirical research in cognitive science will determine the
extent to which that is true.
Van Gelder's characterization of the differences between
the dynamical and computational hypotheses, in terms of the contrast
between change versus state and geometry versus structure, suggests
that the dynamical approach is also at odds with classical mechanism.
Dynamical and mechanistic approaches are in fact allies: mechanism can
identify components whose properties define the variables that are
related in dynamical analyses.
van Gelder argues that computational and dynamical systems
are mathematically distinct kinds of systems. Although there are
real experimental and theoretical differences between adopting a
computational or dynamical perspective on cognition, and the dynamical
approach has much to recommend it, the debate cannot be framed this
rigorously. Instead, what is needed is careful study of concrete
models to improve our intuitions.
Van Gelder presents the dynamical hypothesis as a novel law
of qualitative structure to compete with Newell and Simon's
(1976) physical symbol systems hypothesis. Unlike Newell and
Simon's hypothesis, the dynamical hypothesis fails to provide
necessary and sufficient conditions for cognition. Furthermore,
imprecision in the statement of the dynamical hypothesis renders
Van Gelder's example of a dynamical model is a
Perceptron. The similarity of dynamical models and Perceptrons in turn
exemplifies the close relationship between dynamical and algorithmic
models. Both are models, not literal descriptions of brains. The brain
states of standard modeling are better conceived as processes in the
dynamical sense, but algorithmic models remain useful.
The concept of virtual machine allows us to combine the
dynamical and computational hypotheses in an investigation of
cognition. Van Gelder explicitly rejects this approach, but not only
does it allow us to use the modelling technique most appropriate to
the task, it also opens up a new range of phenomena where these
Van Gelder's specification of the dynamical hypothesis
does not improve on previous notions. All three key attributes of
dynamical systems apply to Turing machines and are hence too general.
However, when a more restricted definition of a dynamical system
is adopted, it becomes clear that the dynamical hypothesis is too
underspecified to constitute an interesting cognitive claim.
(1) Van Gelder's concession that the dynamical hypothesis
is not in opposition to computation in general does not agree well
with his anticomputational stance. (2) There are problems with the
claim that dynamic systems allow for nonrepresentational aspects of
computation in a way in which digital computation cannot. (3) There
are two senses of the “cognition is computation” claim
and van Gelder argues against only one of them. (4) Dynamical systems
as characterized in the target article share problems of universal
realizability with formal notions of computation, but differ in that
there is no solution available for them. (5) The dynamical hypothesis
cannot tell us what cognition is, because instantiating a particular
dynamical system is neither necessary nor sufficient for being a
Dynamics is not enough for cognition, nor it is a substitute
for information-processing aspects of brain behavior. Moreover,
dynamics and computation are not at odds, but are quite compatible.
They can be synthesized so that any dynamical system can be analyzed
in terms of its intrinsic computational components.
For the dynamical hypothesis to be defended as a viable
alternative to a computational perspective on natural cognition,
the role of biological constraints needs to be considered. This task
requires a detailed understanding of the structural organization and
function of the dynamic nervous system, as well as a theoretical
approach that grounds cognitive activity within the constraints of
organism and ecological context.
Van Gelder's hard line against representations is not
supported or supportable, and his soft line in favor of dynamical
systems thinking as a supplement to representational models of
cognition is good advice, but not revolutionary, as he seems to
Research in attitudes and social cognition exemplifies van
Gelder's distinction between the computational and dynamical
approaches. The former emphasizes linear measurement and rational
decision-making. The latter considers processes of associative memory
and self-organization in attitude formation and social influence. The
study of dynamical processes in social cognition has been facilitated
by connectionist approaches to computation.
We argue that the dynamical and computational hypotheses
are compatible and in fact need each other: they are about different
aspects of cognition. However, only computationalism is about the
information-processing aspect. We then argue that any form of
information processing relying on matching and comparing, as
cognition does, must use discrete representations and computations
defined over them.
Van Gelder has presented a position that he ties closely to a
broad class of models known as dynamical models. One can support many
of his broader claims about the importance of this class (as has been
argued by connectionists for quite some time), but there are a number
of unique characteristics of his brand of dynamicism. These
characteristics engender difficulties for his view.
A consideration of underlying neural dynamics and the
evolutionary process producing cognitive agents should complement
the development of dynamical models of behavior. The geometrical
aspects of dynamical systems theory which make it useful in the
description of systems acting in an environment are less useful in
understanding agents interacting with a range of environments,
and may call for supplementation by evolutionary insights.
What new implications does the dynamical hypothesis have
for cognitive science? The short answer is: none. The target article
is basically an attack on traditional symbolic artificial intelligence
(AI) and differs very little from prior connectionist criticisms of
it. For the past 10 years, the connectionist community has been well
aware of the necessity of using (and understanding) dynamically
evolving, recurrent network models of cognition.
Although cognitive psychology is still dominated by
computational theories, there is an emerging emphasis on
dynamical aspects of cognition. Examples are provided supporting
the increased use of dynamically inspired models by psychologists.
Despite measurement and model verification problems in the direct
use of dynamical system theoretic technology, van Gelder's
general approach to cognition is recommended.
Another objection to the dynamical hypothesis is explored. To
resolve it completely, one must focus more directly on an area not
emphasized in van Gelder's discussion: the contributions of
dynamical systems theory to understanding how cognition is neutrally
What van Gelder calls the dynamical hypothesis is only a
special case of what we here dub the general dynamical hypothesis.
His terminology makes it easy to overlook important alternative
dynamical approaches in cognitive science. Connectionist models
typically conform to the general dynamical hypothesis, but not to