15,372 research outputs found
The implications of embodiment for behavior and cognition: animal and robotic case studies
In this paper, we will argue that if we want to understand the function of
the brain (or the control in the case of robots), we must understand how the
brain is embedded into the physical system, and how the organism interacts with
the real world. While embodiment has often been used in its trivial meaning,
i.e. 'intelligence requires a body', the concept has deeper and more important
implications, concerned with the relation between physical and information
(neural, control) processes. A number of case studies are presented to
illustrate the concept. These involve animals and robots and are concentrated
around locomotion, grasping, and visual perception. A theoretical scheme that
can be used to embed the diverse case studies will be presented. Finally, we
will establish a link between the low-level sensory-motor processes and
cognition. We will present an embodied view on categorization, and propose the
concepts of 'body schema' and 'forward models' as a natural extension of the
embodied approach toward first representations.Comment: Book chapter in W. Tschacher & C. Bergomi, ed., 'The Implications of
Embodiment: Cognition and Communication', Exeter: Imprint Academic, pp. 31-5
Social Situatedness: Vygotsky and Beyond
The concept of âsocial situatednessâ, i.e. the idea that the development of individual intelligence requires a social (and cultural) embedding, has recently received much attention in cognitive science and artificial intelligence research. The work of Lev Vygotsky who put forward this view already in the 1920s has influenced the discussion to some degree, but still remains far from well known. This paper therefore aims to give an overview of his cognitive development theory and discuss its relation to more recent work in primatology and socially situated artificial intelligence, in particular humanoid robotics
Virtual Environments for Training: From Individual Learning to Collaboration with Humanoids
The next generation of virtual environments for training is oriented towards
collaborative aspects. Therefore, we have decided to enhance our platform for
virtual training environments, adding collaboration opportunities and
integrating humanoids. In this paper we put forward a model of humanoid that
suits both virtual humans and representations of real users, according to
collaborative training activities. We suggest adaptations to the scenario model
of our platform making it possible to write collaborative procedures. We
introduce a mechanism of action selection made up of a global repartition and
an individual choice. These models are currently being integrated and validated
in GVT, a virtual training tool for maintenance of military equipments,
developed in collaboration with the French company NEXTER-Group
Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics
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