Embodied Cognitive Science is an interdisciplinary field of research, the aim of which is to explain the mechanisms underlying intelligent behavior. It comprises three main methodologies 1) the modeling of psychological and biological systems in a holistic manner that considers the mind and body as a single entity, 2) the formation of a common set of general principles of intelligent behavior, and 3) The experimental use of robotic agents in controlled environments.
Embodied cognitive science borrows heavily from embodied philosophy and the related research fields of cognitive science, psychology, neuroscience and artificial intelligence. From the perspective of neuroscience, research in this field was led by Gerald Edelman of the Neurosciences Institute at La Jolla, the late Francisco Varela of CNRS in France, and J. A. Scott Kelso of FAU. From the perspective of psychology, research by Michael Turvey and Eleanor Rosch. From the perspective of language acquisition, Eric Lenneberg and Philip Rubin at Haskins Laboratories. From the perspective of autonomous agent design, early work is sometimes attributed to Rodney Brooks or Valentino Braitenberg. From the perspective of artificial intelligence, see Understanding Intelligence by Rolf Pfeifer and Christian Scheier or How the body shapes the way we think, also by Rolf Pfeifer and Josh C. Bongard.
In the formation of general principles of intelligent behavior, Pfeifer intended to be contrary to older principles given in Traditional Artificial Intelligence. The most dramatic difference is that the principles are applicable only to situated robotic agents in the real world, a domain where Traditional Artificial Intelligence showed the least promise.
The proposed solutions are as follows, to have the agent exploit the inherent physics of its environment, to exploit the constraints of its niche, and to have agent morphology based on parsimony and the principle of Redundancy. Redundancy reflects the desire for the error-correction of signals afforded by duplicating like channels. Additionally, it reflects the desire to exploit the associations between sensory modalities. (See redundant modalities). In terms of design, this implies that redundancy should be introduced with respect not only to one sensory modality but to several.[4] It has been suggested that the fusion and transfer of knowledge between modalities can be the basis of reducing the size of the sense data taken from the real world.[5] This again addresses the scalability problem.
