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7 - A neuromorphically inspired architecture for cognitive robots

from Part III - Brain-based robots: architectures and approaches

Published online by Cambridge University Press:  05 February 2012

Jeffrey L. Krichmar
Affiliation:
University of California, Irvine
Hiroaki Wagatsuma
Affiliation:
Kyushu Institute of Technology (KYUTECH), Japan
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Summary

Introduction

After several decades of developmental research on intelligent robotics in our lab, we began to focus on the realization of mammalian adaptability functions for our upper-body humanoid robot ISAC (Intelligent Soft Arm Control) described in Kawamura et al. (2000, 2004). Currently, most engineering solutions used in robot designs do not have this level of learning and adaptation. Mammalian adaptability is highly desirable in a robot, because mammals are singularly adaptable goal-directed agents. Mammals learn from experiences with a distinctive degree of flexibility and richness that assures goal accomplishment by a very high proportion of individuals. Thus, in the future, robot capability will be substantially advanced once robots can actively seek goal-directed experiences and learn about new tasks under dynamic and challenging environments.

Seeking inspiration for how to achieve this goal, we look to the mammalian brain; in particular, to the structural and functional commonalities observed across mammalian species. From rodents to humans, mammals share many neural mechanisms and control processes relevant to adaptability. Mammals typically accomplish goals in a timely fashion, in situations from the familiar to the new and challenging. Moreover, mammals learn how to function effectively, with few innate capabilities and with little or no supervision of their learning. Albeit with many gaps in knowledge of what makes the human brain distinctively capable, enough seems to be known about the whole mammalian brain to inform architectural analysis and embodied modeling of mammalian brains.

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Publisher: Cambridge University Press
Print publication year: 2011

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