Robot regulatory behaviour based on fundamental homeostatic and allostatic principles

Animals in their ecological context behave not only in response to external events, such as opportunities and threats but also according to their internal needs. As a result, the survival of the organism is achieved through regulatory behaviour. Although homeostatic and allostatic principles play an...

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Detalles Bibliográficos
Autores: Guerrero-Rosado, Oscar, Verschure, Paul F. M. J.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2021
País:España
Institución:Universitat Pompeu Fabra
Repositorio:Repositorio Digital de la UPF
OAI Identifier:oai:repositori.upf.edu:10230/55875
Acceso en línea:http://hdl.handle.net/10230/55875
http://dx.doi.org/10.1016/j.procs.2021.06.039
Access Level:acceso abierto
Palabra clave:Allostasis
Homeostasis
Regulatory Behaviour
Action Selection
Reticular Formation
Cognitive Architecture
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spelling Robot regulatory behaviour based on fundamental homeostatic and allostatic principlesGuerrero-Rosado, OscarVerschure, Paul F. M. J.AllostasisHomeostasisRegulatory BehaviourAction SelectionReticular FormationCognitive ArchitectureAnimals in their ecological context behave not only in response to external events, such as opportunities and threats but also according to their internal needs. As a result, the survival of the organism is achieved through regulatory behaviour. Although homeostatic and allostatic principles play an important role in such behaviour, how an animal’s brain implements these principles is not fully understood yet. In this paper, we propose a new model of regulatory behaviour inspired by the functioning of the medial Reticular Formation (mRF). This structure is spread throughout the brainstem and has shown generalized Central Nervous System (CNS) arousal control and fundamental action-selection properties. We propose that a model based on the mRF allows the flexibility needed to be implemented in diverse domains, while it would allow integration of other components such as place cells to enrich the agent’s performance. Such a model will be implemented in a mobile robot that will navigate replicating the behaviour of the sand-diving lizard, a benchmark for regulatory behaviour.This work has received funding from the Horizon 2020 under grant agreement of the project ReHyb, ID: 871767; and of the project HR-Recycler ID: 820742.Elsevier202320232021info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://hdl.handle.net/10230/55875http://dx.doi.org/10.1016/j.procs.2021.06.039reponame:Repositorio Digital de la UPFinstname:Universitat Pompeu FabraInglésProcedia Computer Science. 2021;190:292-300.info:eu-repo/grantAgreement/EC/H2020/871767info:eu-repo/grantAgreement/EC/H2020/820742© 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)https://creativecommons.org/licenses/by-nc-nd/4.0info:eu-repo/semantics/openAccessoai:repositori.upf.edu:10230/558752026-06-12T07:21:37Z
dc.title.none.fl_str_mv Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
title Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
spellingShingle Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
Guerrero-Rosado, Oscar
Allostasis
Homeostasis
Regulatory Behaviour
Action Selection
Reticular Formation
Cognitive Architecture
title_short Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
title_full Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
title_fullStr Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
title_full_unstemmed Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
title_sort Robot regulatory behaviour based on fundamental homeostatic and allostatic principles
dc.creator.none.fl_str_mv Guerrero-Rosado, Oscar
Verschure, Paul F. M. J.
author Guerrero-Rosado, Oscar
author_facet Guerrero-Rosado, Oscar
Verschure, Paul F. M. J.
author_role author
author2 Verschure, Paul F. M. J.
author2_role author
dc.subject.none.fl_str_mv Allostasis
Homeostasis
Regulatory Behaviour
Action Selection
Reticular Formation
Cognitive Architecture
topic Allostasis
Homeostasis
Regulatory Behaviour
Action Selection
Reticular Formation
Cognitive Architecture
description Animals in their ecological context behave not only in response to external events, such as opportunities and threats but also according to their internal needs. As a result, the survival of the organism is achieved through regulatory behaviour. Although homeostatic and allostatic principles play an important role in such behaviour, how an animal’s brain implements these principles is not fully understood yet. In this paper, we propose a new model of regulatory behaviour inspired by the functioning of the medial Reticular Formation (mRF). This structure is spread throughout the brainstem and has shown generalized Central Nervous System (CNS) arousal control and fundamental action-selection properties. We propose that a model based on the mRF allows the flexibility needed to be implemented in diverse domains, while it would allow integration of other components such as place cells to enrich the agent’s performance. Such a model will be implemented in a mobile robot that will navigate replicating the behaviour of the sand-diving lizard, a benchmark for regulatory behaviour.
publishDate 2021
dc.date.none.fl_str_mv 2021
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10230/55875
http://dx.doi.org/10.1016/j.procs.2021.06.039
url http://hdl.handle.net/10230/55875
http://dx.doi.org/10.1016/j.procs.2021.06.039
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Procedia Computer Science. 2021;190:292-300.
info:eu-repo/grantAgreement/EC/H2020/871767
info:eu-repo/grantAgreement/EC/H2020/820742
dc.rights.none.fl_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositorio Digital de la UPF
instname:Universitat Pompeu Fabra
instname_str Universitat Pompeu Fabra
reponame_str Repositorio Digital de la UPF
collection Repositorio Digital de la UPF
repository.name.fl_str_mv
repository.mail.fl_str_mv
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