Mind, Body, World- Foundations of Cognitive Science, 2013a

the non-cognitive that does justice to the subject matter of cognitive psychology.
(Adams & Aizawa, 2008, p. 11)
A variety of other critiques can be found in various contributions to Robbins and
Aydede’s (2009) Cambridge Handbook of Situated Cognition. Prinz made a pointed
argument that the extended mind has nothing to contribute to the study of consciousness.
Rupert noted how the notion of innateness poses numerous problems
for the extended mind. Warneken and Tomasello examined cultural scaffolding, but
they eventually adopted a position where these cultural tools have been internalized
by agents. Finally, Bechtel presented a coherent argument from the philosophy of
biology that there is good reason for the skull to serve as the boundary between the
world and the mind. Clearly, the degree to which extendedness is adopted by situated
researchers is far from universal.
In spite of the currently unresolved debate about the plausibility of the
extended mind, the extended mind hypothesis is an idea that is growing in popularity
in embodied cognitive science. Let us briefly turn to another implication that
this hypothesis has for the practice of cognitive science.
The extended mind hypothesis is frequently applied to single cognitive agents.
However, this hypothesis also opens the door to co-operative or public cognition in
which a group of agents are embedded in a shared environment (Hutchins, 1995).
In this situation, more than one cognitive agent can manipulate the world that is
being used to support the information processing of other group members.
Hutchins (1995) provided one example of public cognition in his description
of how a team of individuals is responsible for navigating a ship. He argued that
“organized groups may have cognitive properties that differ from those of the individuals
who constitute the group” (p. 228). For instance, in many cases it is very difficult
to translate the heuristics used by a solo navigator into a procedure that can
be implemented by a navigation team.
Collective intelligence—also called swarm intelligence or co-operative computing—is
also of growing importance in robotics. Entomologists used the concept
of the superorganism (Wheeler, 1911) to explain how entire colonies could produce
more complex results (such as elaborate nests) than one would predict from
knowing the capabilities of individual colony members. Swarm intelligence is an
interesting evolution of the idea of the superorganism; it involves a collective of
agents operating in a shared environment. Importantly, a swarm’s components are
only involved in local interactions with each other, resulting in many advantages
(Balch & Parker, 2002; Sharkey, 2006).
For instance, a computing swarm is scalable—it may comprise varying numbers
of agents, because the same control structure (i.e., local interactions) is used
regardless of how many agents are in the swarm. For the same reason, a computing
swarm is flexible: agents can be added or removed from the swarm without
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