TY - GEN
T1 - A novel hierarchical constructive BackPropagation with memory for teaching a robot the names of things
AU - Alnajjar, Fady
AU - Hafiz, Abdul Rahman
AU - Murase, Kazuyuki
PY - 2009
Y1 - 2009
N2 - In recent years, there has been a growing attention to develop a Human-like Robot controller that hopes to move the robots closer to face real world applications. Several approaches have been proposed to support the learning phase in such a controller, such as learning through observation and\or a direct guidance from the user. These approaches, however, require incremental learning and memorizing techniques, where the robot can design its internal system and keep retraining it overtime. This study, therefore, investigates a new idea to develop incremental learning and memory model, we called, a Hierarchical Constructive BackPropagation with Memory (HCBPM). The validity of the model was tested in teaching a robot a group of names (colors). The experimental results indicate the efficiency of the model to build a social learning environment between the user and the robot. The robot could learn various color names and its different phases, and retrieve these data easily to teach another user what it had learned.
AB - In recent years, there has been a growing attention to develop a Human-like Robot controller that hopes to move the robots closer to face real world applications. Several approaches have been proposed to support the learning phase in such a controller, such as learning through observation and\or a direct guidance from the user. These approaches, however, require incremental learning and memorizing techniques, where the robot can design its internal system and keep retraining it overtime. This study, therefore, investigates a new idea to develop incremental learning and memory model, we called, a Hierarchical Constructive BackPropagation with Memory (HCBPM). The validity of the model was tested in teaching a robot a group of names (colors). The experimental results indicate the efficiency of the model to build a social learning environment between the user and the robot. The robot could learn various color names and its different phases, and retrieve these data easily to teach another user what it had learned.
KW - Constructive backpropagation
KW - Human-like robot controller
KW - Incremental learning and memory
UR - http://www.scopus.com/inward/record.url?scp=76649116537&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=76649116537&partnerID=8YFLogxK
U2 - 10.1007/978-3-642-10677-4_51
DO - 10.1007/978-3-642-10677-4_51
M3 - Conference contribution
AN - SCOPUS:76649116537
SN - 3642106765
SN - 9783642106767
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 451
EP - 459
BT - Neural Information Processing - 16th International Conference, ICONIP 2009, Proceedings
T2 - 16th International Conference on Neural Information Processing, ICONIP 2009
Y2 - 1 December 2009 through 5 December 2009
ER -