Modeling the Role of Energy Management in Embodied Cognition

• The quest for adaptive and autonomous robots, flexible enough to smoothly comply with unstructured environments and operate in close interaction with humans, seems to require a deep rethinking of classical engineering methods. The adaptivity of natural organisms, whose cognitive capacities are rooted in their biological organization, is an obvious source of inspiration. While approaches that highlight the role of embodiment in both cognitive science and cognitive robotics are gathering momentum, the crucial role of internal bodily processes as foundational components of the biological mind is still largely neglected.This thesis advocates a perspective on embodiment that emphasizes the role of non-neural bodily dynamics in the constitution of cognitive processes in both natural and artificial systems. In the first part, it critically examines the theoretical positions that have influenced current theories and the author's own position. The second part presents the author's experimental work, based on the computer simulation of simple robotic agents engaged in energy-related tasks. Proto-metabolic dynamics, modeled on the basis of actual microbial fuel cells for energy generation, constitute the foundations of a powerful motivational engine. Following a history of adaptation, proto-metabolic states bias the robot towards specific subsets of behaviors, viably attuned to the current context, and facilitate a swift re-adaptation to novel tasks. Proto-metabolic dynamics put the situated nature of the agent-environment sensorimotor interaction within a perspective that is functional to the maintenance of the robot's overall `survival'. Adaptive processes tend to convert metabolic constraints into opportunities, branching into a rich and energetically viable behavioral diversity.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

Technology

Teknik

Publication and Content Type

vet (subject category)

dok (subject category)