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Living machinesA handbook of research in biomimetics and biohybrid systems$
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Tony J. Prescott, Nathan Lepora, and Paul F.M.J Verschure

Print publication date: 2018

Print ISBN-13: 9780199674923

Published to Oxford Scholarship Online: June 2018

DOI: 10.1093/oso/9780199674923.001.0001

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A chronology of Distributed Adaptive Control

A chronology of Distributed Adaptive Control

Chapter:
(p.346) Chapter 36 A chronology of Distributed Adaptive Control
Source:
Living machines
Author(s):

Paul F. M. J. Verschure

Publisher:
Oxford University Press
DOI:10.1093/oso/9780199674923.003.0036

This chapter presents the Distributed Adaptive Control (DAC) theory of the mind and brain of living machines. DAC provides an explanatory framework for biological brains and an integration framework for synthetic ones. DAC builds on several themes presented in the handbook: it integrates different perspectives on mind and brain, exemplifies the synthetic method in understanding living machines, answers well-defined constraints faced by living machines, and provides a route for the convergent validation of anatomy, physiology, and behavior in our explanation of biological living machines. DAC addresses the fundamental question of how a living machine can obtain, retain, and express valid knowledge of its world. We look at the core components of DAC, specific benchmarks derived from the engagement with the physical and the social world (the H4W and the H5W problems) in foraging and human–robot interaction tasks. Lastly we address how DAC targets the UTEM benchmark and the relation with contemporary developments in AI.

Keywords:   Distributed Adaptive Control, problem of priors, symbol grounding problem, convergent validation, foraging, brain, architecture, system

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