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266 WEBER & VOSGERAU
equations. 1 Such a view is also supported by Brook’s (1991) research in robotics and in
artificial life because his findings can be applied to explain adaptive behavior without any
strong notion of representation. Brooks insists: “Representation is the wrong unit of
abstraction in building the bulkiest parts of intelligent systems” (Brooks 1991: 140), because
“the world is its own best model” (Brooks 1990: 6). Those authors do not postulate the
existence of an internal representational model of a cognitive system that guides its behavior
and its actions. Moreover, they reject the idea that a cognitive system ought to be conceived of
as relatively independent from the world in its ability to representationally reproduce the
external structure of the environment to guide its behavior.
But many still suspect that in developing an adequate theory of cognition, especially as
regards belief formation and action planning, we need to postulate internal mental
representations. For example, at first sight a theory of dynamical interaction between an
organism and its environment alone provides no satisfying explanation when it comes to
anticipatory behavior. A dynamical systems theory may face serious difficulties in providing
an account of how systems are able to deal with “representation-hungry” tasks, such as those
involving abstract thought and high-level reasoning. Cognitive processes like problem solving,
planning, language acquisition, thinking about absent, even non-existent states of affairs,
counterfactual reasoning and learning in general which are all conceived of as cases of purely
internal processing in this context seem most naturally explained by appeal to internal
representations (cf. Clark and Toribio 1994). So, the essential challenge is to explain those
aspects of behavior that involve internal factors beyond immediate interaction.
We further want to pay attention to the relation between perception, action and cognition as
conceived in dynamical approaches. For instance, Thelen et al. state that “cognition depends
on the kinds of experiences that come from having a body with particular perceptual and
motor capabilities that are inseparably linked” (2001: 1; emphasis added by the authors). But
what does “inseparably linked” or “depend” mean for the mutual contribution of the domains
or “capabilities” of perception, action and cognition while cognition is – in some not yet
specified sense – “embodied”? What do we learn about the nature or architecture of the mind,
its functional makeup and its relation to bodily functions? Is cognition in this sense
“embodied” that it is entirely dependent of sensorimotor processes?
An adequate theory of embodied cognition ought to allow for a further understanding of the
nature of mental representations. An alternative and more moderate (qua
representationalist) view in embodied cognitive science is a project called “grounded
cognition” (Barsalou 1999, 2008). Therefore, we discern that the major outstanding issues
center on the representationalist understanding of grounded cognition in contrast to antirepresentationalist
conceptions of embodied cognition. The idea of grounded cognition is that
cognitive and perceptual mechanisms share the same representational states: the core
sources of representation that “ground” cognition are thought of as simulations in the brain’s
modal systems such as the sensorimotor system. Contrary to the language of thought
hypothesis, the theory especially challenges the view that core representations are amodal
symbols and data structures processed independently of the brain’s modal systems for
perception, action, and introspection. Barsalou summarizes the project of grounded cognition
as follows:
Grounded cognition rejects traditional views that cognition is computation on amodal
symbols in a modular system, independent of the brain’s modal systems for perception,
1
This is not to claim that every possible dynamical account like the dynamical systems theory is per se
an anti-representationalist view. There are works rebuilding and integrating even an elaborated notion
of representation in dynamic approaches; for example, Spivey’s “attempt to raise awareness of the
benefits of emphasizing continuous processing, and therefore continuous representation as well”
(Spivey 2007: 3) suggests some kind of “symbolic dynamics” (2007: 262 ff.), thereby reconsidering
symbolic, but not computational representations.