Generating rescheduling knowledge using reinforcement learning in a cognitive architecture

In order to reach higher degrees of flexibility, adaptability and autonomy in manufacturing systems, it is essential to develop new rescheduling methodologies which resort to cognitive capabilities, similar to those found in human beings. Artificial cognition is important for designing planning and...

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Detalles Bibliográficos
Autores principales:	Palombarini, Jorge, Barsce, Juan Cruz, Martínez, Ernesto
Formato:	Objeto de conferencia
Lenguaje:	Inglés
Publicado:	2014
Materias:	Ciencias Informáticas rescheduling cognitive architecture manofacturing systems reinforcement learing soar Inteligencia Artificial
Acceso en línea:	http://sedici.unlp.edu.ar/handle/10915/41737 http://43jaiio.sadio.org.ar/proceedings/ASAI/15.pdf
Aporte de:	SEDICI (UNLP) de Universidad Nacional de La Plata

id	I19-R120-10915-41737
record_format	dspace
institution	Universidad Nacional de La Plata
institution_str	I-19
repository_str	R-120
collection	SEDICI (UNLP)
language	Inglés
topic	Ciencias Informáticas rescheduling cognitive architecture manofacturing systems reinforcement learing soar Inteligencia Artificial
spellingShingle	Ciencias Informáticas rescheduling cognitive architecture manofacturing systems reinforcement learing soar Inteligencia Artificial Palombarini, Jorge Barsce, Juan Cruz Martínez, Ernesto Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
topic_facet	Ciencias Informáticas rescheduling cognitive architecture manofacturing systems reinforcement learing soar Inteligencia Artificial
description	In order to reach higher degrees of flexibility, adaptability and autonomy in manufacturing systems, it is essential to develop new rescheduling methodologies which resort to cognitive capabilities, similar to those found in human beings. Artificial cognition is important for designing planning and control systems that generate and represent knowledge about heuristics for repairbased scheduling. Rescheduling knowledge in the form of decision rules is used to deal with unforeseen events and disturbances reactively in real time, and take advantage of the ability to act interactively with the user to counteract the effects of disruptions. In this work, to achieve the aforementioned goals, a novel approach to generate rescheduling knowledge in the form of dynamic first-order logical rules is proposed. The proposed approach is based on the integration of reinforcement learning with artificial cognitive capabilities involving perception and reasoning/learning skills embedded in the Soar cognitive architecture. An industrial example is discussed showing that the approach enables the scheduling system to assess its operational range in an autonomic way, and to acquire experience through intensive simulation while performing repair tasks.
format	Objeto de conferencia Objeto de conferencia
author	Palombarini, Jorge Barsce, Juan Cruz Martínez, Ernesto
author_facet	Palombarini, Jorge Barsce, Juan Cruz Martínez, Ernesto
author_sort	Palombarini, Jorge
title	Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
title_short	Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
title_full	Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
title_fullStr	Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
title_full_unstemmed	Generating rescheduling knowledge using reinforcement learning in a cognitive architecture
title_sort	generating rescheduling knowledge using reinforcement learning in a cognitive architecture
publishDate	2014
url	http://sedici.unlp.edu.ar/handle/10915/41737 http://43jaiio.sadio.org.ar/proceedings/ASAI/15.pdf
work_keys_str_mv	AT palombarinijorge generatingreschedulingknowledgeusingreinforcementlearninginacognitivearchitecture AT barscejuancruz generatingreschedulingknowledgeusingreinforcementlearninginacognitivearchitecture AT martinezernesto generatingreschedulingknowledgeusingreinforcementlearninginacognitivearchitecture
bdutipo_str	Repositorios
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Generating rescheduling knowledge using reinforcement learning in a cognitive architecture

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