Towards a “Brain-Guided” Cognitive Architecture - Bioinspired Approaches for Human-Centric Technologies - page 197

purposive system that emerges from a persistent flux of fragmented, partially
inconsistent episodes in which the human/humanoid perceives, acts, learns, remem-
bers, forgets, reasons, makes mistakes, introspects, etc. We aim at linking such a
model building approach with emerging trends in neuroscience, taking into account
that one of the fundamental challenges today is to “causally and computationally”
correlate the incredibly complex behavior of animals to the equally complex
activity in their brains. This requires to build a shared computational/neural basis
for “execution, imagination, and understanding” of action, while taking into
account recent findings from the field of “connectomics,” which addresses the
large-scale organization of the cerebral cortex, and the discovery of the “default
mode network” of the brain. We will particularly focus, in the near future, on the
organization of memory instead of “learning” per se because this helps understand-
ing development from a more “holistic” viewpoint that is not restricted to “isolated
tasks” or “experiments.” Computationally the proposed architecture should lead
towards novel nonlinear, non-Turing computational machinery based on quasi-
physical, non-digital interactions grounded in the biology of the brain.
7.2 Background Concepts on Body and Embodiment
7.2.1 Embodiment
Robotics has long been disputed between approaches that are fully dependent on the
exploitation of the affordances provided by the specific features/structure of the
robot “body” and approaches, based on artificial intelligence (AI) principles, that
neglect “embodiment” and operate in a completely abstract domain. The “vehicles”
proposed by Valentino Braitenberg ( 1986 ) are examples of the former approach: in
spite of the fact that the control hardware is simply a reactive system, which directly
links the sensors to the actuators, vehicles' behaviors can be surprisingly adaptive
and exhibit remarkable features that are commonly attributed to some kind of
“intelligence.” There are also many biological counterparts of Braitenberg's vehi-
cles, such as the Aplysia depilans (Kandel and Tauc 1965 ), which emphasize the
fact that adaptive behavior does not require a central nervous system but can
emerge in very simple networks of biological neurons as well. However, it is
quite clear that purely reactive systems (or reflexes, in the neurophysiological
jargon) can only work effectively with very simple bodies.
Nevertheless, a very influential theory proposed by Charles Sherrington ( 1904 )
that dominated the understanding of human neurophysiology for over half a century
is based on a simple generalization of the reactive architecture, by positing that
reflexes are the basic modules of the integrative action of the nervous system, thus
enabling the entire body to function towards one definite goal at a time. A similar
point of view was defended by Rodney Brooks in robotics (Brooks 1991 ), as a
drastic alternative to GOFAI (Good Old-Fashioned Artificial Intelligence), by