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Paladyn, Journal of Behavioral Robotics

Editor-in-Chief: Schöner, Gregor


Covered by SCOPUS


CiteScore 2018: 2.17

SCImago Journal Rank (SJR) 2018: 0.336
Source Normalized Impact per Paper (SNIP) 2018: 1.707

ICV 2017: 99.90

Open Access
Online
ISSN
2081-4836
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The dynamics of neural activation variables

Hendrik Reimann / Jonas Lins / Gregor Schöner
Published Online: 2015-03-11 | DOI: https://doi.org/10.1515/pjbr-2015-0003

Abstract

This paper presents a comprehensive and detailed analysis of the elementary building blocks of neurally inspired architectures for cognitive robotics. It provides a brief outline of the fundamental principles by which biological nervous systems link to the environment in terms of perception, cognition, and behavior. We describe a class of dynamic neural activation variable based on these principles. We show that these dynamic neurons have the appropriate stability properties.Adding even simple connections between a small number of nodes is sufficient to constitute systems that make important decisions. Going through these mechanisms in detail, this paper should facilitate the design of neurally inspired architectures for behavior generation in robotic agents.

Keywords : Cognitive Robotics; Neural Dynamics; Bifurcations; Neural Networks

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About the article

Received: 2014-01-17

Accepted: 2015-01-17

Published Online: 2015-03-11


Citation Information: Paladyn, Journal of Behavioral Robotics, Volume 6, Issue 1, ISSN (Online) 2081-4836, DOI: https://doi.org/10.1515/pjbr-2015-0003.

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© 2015 Hendrik Reimann et al.. This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License. BY-NC-ND 3.0

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