Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study
Autor(a) principal: | |
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Data de Publicação: | 2011 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/1822/11987 |
Resumo: | In this paper we present a model for action preparation and decision making in cooperative tasks that is inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. It implements the coordination of actions and goals among the partners as a dynamic process that integrates contextual cues, shared task knowledge and predicted outcome of others’ motor behavior. The control architecture is formalized by a system of coupled dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode task-relevant information about action means, task goals and context in the form of self-sustained activation pat- terns. These patterns are triggered by input from connected populations and evolve continuously in time under the influence of recurrent interactions. The dynamic model of joint action is evaluated in a task in which a robot and a human jointly construct a toy object. We show that the highly context sensitive mapping from action observation onto appropriate complementary actions allows coping with dynamically changing joint action situations. |
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Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction studyMotor planningDecision makingDynamic neural fieldsJoint actionHuman-robot interactionHuman-robot collaborationScience & TechnologySocial SciencesIn this paper we present a model for action preparation and decision making in cooperative tasks that is inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. It implements the coordination of actions and goals among the partners as a dynamic process that integrates contextual cues, shared task knowledge and predicted outcome of others’ motor behavior. The control architecture is formalized by a system of coupled dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode task-relevant information about action means, task goals and context in the form of self-sustained activation pat- terns. These patterns are triggered by input from connected populations and evolve continuously in time under the influence of recurrent interactions. The dynamic model of joint action is evaluated in a task in which a robot and a human jointly construct a toy object. We show that the highly context sensitive mapping from action observation onto appropriate complementary actions allows coping with dynamically changing joint action situations.The present research was conducted in the context of the fp6-IST2 EU-IP Project JAST (Project No. 003747) and partly financed by the FCT grants POCl/V.5/A0119/2005 and CONC-REEQ/17/2001. We would like to thank Profs. Harold Bekkering and Ruud Meulenbroek for the numerous discussions, and Emanuel Sousa, Flora Ferreira, Nzoji Hipolito, Rui Silva and Toni Machado for their help during the robotic experiments. We also thank the anonymous reviewers for their insightful comments and feedback on how to improve the manuscript.ElsevierUniversidade do MinhoBicho, E.Erlhagen, WolframLouro, LuísSilva, Eliana Oliveira Costa2011-01-032011-01-03T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/1822/11987eng"Human Movement Science". ISSN 0167-9457. (Jan. 2011)0167-945710.1016/j.humov.2010.08.01221208673http://www.elsevier.com/wps/find/journaldescription.cws_home/505584/description#descriptioninfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-21T12:38:58Zoai:repositorium.sdum.uminho.pt:1822/11987Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T19:35:31.424519Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
title |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
spellingShingle |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study Bicho, E. Motor planning Decision making Dynamic neural fields Joint action Human-robot interaction Human-robot collaboration Science & Technology Social Sciences |
title_short |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
title_full |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
title_fullStr |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
title_full_unstemmed |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
title_sort |
Neuro-cognitive mechanisms of decision making in joint action: A human-robot interaction study |
author |
Bicho, E. |
author_facet |
Bicho, E. Erlhagen, Wolfram Louro, Luís Silva, Eliana Oliveira Costa |
author_role |
author |
author2 |
Erlhagen, Wolfram Louro, Luís Silva, Eliana Oliveira Costa |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Universidade do Minho |
dc.contributor.author.fl_str_mv |
Bicho, E. Erlhagen, Wolfram Louro, Luís Silva, Eliana Oliveira Costa |
dc.subject.por.fl_str_mv |
Motor planning Decision making Dynamic neural fields Joint action Human-robot interaction Human-robot collaboration Science & Technology Social Sciences |
topic |
Motor planning Decision making Dynamic neural fields Joint action Human-robot interaction Human-robot collaboration Science & Technology Social Sciences |
description |
In this paper we present a model for action preparation and decision making in cooperative tasks that is inspired by recent experimental findings about the neurocognitive mechanisms supporting joint action in humans. It implements the coordination of actions and goals among the partners as a dynamic process that integrates contextual cues, shared task knowledge and predicted outcome of others’ motor behavior. The control architecture is formalized by a system of coupled dynamic neural fields representing a distributed network of local but connected neural populations. Different pools of neurons encode task-relevant information about action means, task goals and context in the form of self-sustained activation pat- terns. These patterns are triggered by input from connected populations and evolve continuously in time under the influence of recurrent interactions. The dynamic model of joint action is evaluated in a task in which a robot and a human jointly construct a toy object. We show that the highly context sensitive mapping from action observation onto appropriate complementary actions allows coping with dynamically changing joint action situations. |
publishDate |
2011 |
dc.date.none.fl_str_mv |
2011-01-03 2011-01-03T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/1822/11987 |
url |
http://hdl.handle.net/1822/11987 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
"Human Movement Science". ISSN 0167-9457. (Jan. 2011) 0167-9457 10.1016/j.humov.2010.08.012 21208673 http://www.elsevier.com/wps/find/journaldescription.cws_home/505584/description#description |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799132881560272896 |