Autonomous Robots Based on Inspiration From Biology: The Relation to Neuroinformatics

Author: Arbib, Michael A

Source: Neuroinformatics, Volume 3, Number 3, September 2005 , pp. 281-286(6)

Publisher: Humana Press

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Abstract:

Amari et al. (2003) set forth the following points concerning neuroinformatics and the brain: • The brain stores and processes information and controls a wide range of behaviors, enabling animals and humans to survive in complex, changing environments. The full study of the brain must address its embodiment— yielding the behavior of individuals (both animals and humans) and supporting patterns of social interaction. • The brain’s “computations” are very different from those of modern computers. Understanding the brain may thus contribute novel methodologies to modern information science and technology. • Computational neuroscience plays an increasingly important role in making sense of the brain’s complexities. Nonetheless, the flood of data from empirical neuroscience, at many levels from molecules to cells to networks and organisms, requires that modeling be complemented by deep insights into the storage, retrieval and analysis of masses of heterogeneous data. • Applications of modeling and database support for neuroscience have come together to create Neuroinformatics. The present issue of the journal Neuroinformatics is devoted to the theme of “Neurorobotic Models in Neuroscience and Neuroinformatics.” As Anil Seth, Olaf Sporns, and Jeff Krichmar (Seth et al., 2005) state in their Editorial, a neurorobotic device engages in a behavioral task; is situated in a structured environment; and has its behavior controlled in a way that reflects, at some level, the brain’s architecture and dynamics. Although this issue has little to say about the database end of neuroinformatics, it does engage strongly with the brain’s embodiment, contributing to computational neuroscience and suggesting novel methodologies for information science and technology. The study of autonomous robots based on inspiration from biology (Damper et al., 2000) can contribute to neuroinformatics because, in the words of the editors, they “provide heuristics for developing and testing theories of brain function in the context of phenotypic and environmental interactions [as well as] . . . a foundation for the development of more effective robots.”

Document Type: Miscellaneous

Publication date: 2005-09-01

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