Learning of shared attention in sociable robotics
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
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Data(s) |
20/10/2012
20/10/2012
2009
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Resumo |
Sociable robots are embodied agents that are part of a heterogeneous society of robots and humans. They Should be able to recognize human beings and each other, and to engage in social, interactions. The use of a robotic architecture may strongly reduce the time and effort required to construct a sociable robot. Such architecture must have structures and mechanisms to allow social interaction. behavior control and learning from environment. Learning processes described oil Science of Behavior Analysis may lead to the development of promising methods and Structures for constructing robots able to behave socially and learn through interactions from the environment by a process of contingency learning. In this paper, we present a robotic architecture inspired from Behavior Analysis. Methods and structures of the proposed architecture, including a hybrid knowledge representation. are presented and discussed. The architecture has been evaluated in the context of a nontrivial real problem: the learning of the shared attention, employing an interactive robotic head. The learning capabilities of this architecture have been analyzed by observing the robot interacting with the human and the environment. The obtained results show that the robotic architecture is able to produce appropriate behavior and to learn from social interaction. (C) 2009 Elsevier Inc. All rights reserved. Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) FAPESP CNPq Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) |
Identificador |
JOURNAL OF ALGORITHMS-COGNITION INFORMATICS AND LOGIC, v.64, n.4, p.139-151, 2009 0196-6774 http://producao.usp.br/handle/BDPI/28770 10.1016/j.jalgor.2009.04.005 |
Idioma(s) |
eng |
Publicador |
ACADEMIC PRESS INC ELSEVIER SCIENCE |
Relação |
Journal of Algorithms-cognition Informatics and Logic |
Direitos |
restrictedAccess Copyright ACADEMIC PRESS INC ELSEVIER SCIENCE |
Palavras-Chave | #Sociable robotics #Shared attention #Reinforcement learning #JOINT ATTENTION #MODEL #Computer Science, Theory & Methods #Mathematics, Applied |
Tipo |
article original article publishedVersion |