Learning in real robots from environment interaction
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http://hdl.handle.net/10045/21361
Título: | Learning in real robots from environment interaction |
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Autor/es: | Quintía Vidal, Pablo | Iglesias Rodríguez, Roberto | Rodríguez González, Miguel Ángel | Vázquez Regueiro, Carlos | Valdés Villarrubia, Fernando |
Palabras clave: | Continuous robot learning | Robot adaptation | Learning from environment interaction | Reinforcement learning |
Área/s de conocimiento: | Ciencia de la Computación e Inteligencia Artificial |
Fecha de publicación: | ene-2012 |
Editor: | Red de Agentes Físicos |
Cita bibliográfica: | QUINTÍA, P., et al. “Learning in real robots from environment interaction”. Journal of Physical Agents. Vol. 6, No. 1 (Jan. 2012). ISSN 1888-0258, pp. 43-51 |
Resumen: | This article describes a proposal to achieve fast robot learning from its interaction with the environment. Our proposal will be suitable for continuous learning procedures as it tries to limit the instability that appears every time the robot encounters a new situation it had not seen before. On the other hand, the user will not have to establish a degree of exploration (usual in reinforcement learning) and that would prevent continual learning procedures. Our proposal will use an ensemble of learners able to combine dynamic programming and reinforcement learning to predict when a robot will make a mistake. This information will be used to dynamically evolve a set of control policies that determine the robot actions. |
Patrocinador/es: | This work was supported by the research grants TIN2009-07737 and INCITE08PXIB262202PR. |
URI: | http://hdl.handle.net/10045/21361 | http://dx.doi.org/10.14198/JoPha.2012.6.1.06 |
ISSN: | 1888-0258 |
DOI: | 10.14198/JoPha.2012.6.1.06 |
Idioma: | eng |
Tipo: | info:eu-repo/semantics/article |
Revisión científica: | si |
Aparece en las colecciones: | Journal of Physical Agents - 2012, Vol. 6, No. 1 |
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JoPha_6_1_06.pdf | 3,35 MB | Adobe PDF | Abrir Vista previa | |
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