Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control
A biologically inspired mechanism for robot action selection, based on the vertebrate basal ganglia, has been previously presented (Prescott et al. 2006, Montes Gonzalez et al. 2000). In this model the task confronting the robot is decomposed into distinct behavioural modules that integrate informat...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2007-01-01
|
| Series: | Applied Bionics and Biomechanics |
| Online Access: | http://dx.doi.org/10.1080/11762320701492792 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850169893246205952 |
|---|---|
| author | F. Montes-Gonzalez T. J. Prescott J. Negrete-Martinez |
| author_facet | F. Montes-Gonzalez T. J. Prescott J. Negrete-Martinez |
| author_sort | F. Montes-Gonzalez |
| collection | DOAJ |
| description | A biologically inspired mechanism for robot action selection, based on the vertebrate basal ganglia, has been previously presented (Prescott et al. 2006, Montes Gonzalez et al. 2000). In this model the task confronting the robot is decomposed into distinct behavioural modules that integrate information from multiple sensors and internal state to form ‘salience’ signals. These signals are provided as inputs to a computational model of the basal ganglia whose intrinsic processes cause the selection by disinhibition of a winning behaviour. This winner is then allowed access to the motor plant whilst losing behaviours are suppressed. In previous research we have focused on the development of this biomimetic selection architecture, and have therefore used behavioural modules that were hand-coded as algorithmic procedures. In the current article, we demonstrate the use of genetic algorithms and gradient–descent learning to automatically generate/tune some of the modules that generate the model behaviour. |
| format | Article |
| id | doaj-art-a57602a333a74f9991ae5b51b2b3d7e9 |
| institution | OA Journals |
| issn | 1176-2322 1754-2103 |
| language | English |
| publishDate | 2007-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Applied Bionics and Biomechanics |
| spelling | doaj-art-a57602a333a74f9991ae5b51b2b3d7e92025-08-20T02:20:37ZengWileyApplied Bionics and Biomechanics1176-23221754-21032007-01-014310110910.1080/11762320701492792Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot ControlF. Montes-Gonzalez0T. J. Prescott1J. Negrete-Martinez2Department of Artificial Intelligence, Universidad Veracruzana, Sebastian Camacho 5, Xalapa, Veracruz, MexicoDepartment of Psychology, University of Sheffield, Western Bank, Sheffield S10 2TN, UKDepartment of Artificial Intelligence, Universidad Veracruzana, Sebastian Camacho 5, Xalapa, Veracruz, MexicoA biologically inspired mechanism for robot action selection, based on the vertebrate basal ganglia, has been previously presented (Prescott et al. 2006, Montes Gonzalez et al. 2000). In this model the task confronting the robot is decomposed into distinct behavioural modules that integrate information from multiple sensors and internal state to form ‘salience’ signals. These signals are provided as inputs to a computational model of the basal ganglia whose intrinsic processes cause the selection by disinhibition of a winning behaviour. This winner is then allowed access to the motor plant whilst losing behaviours are suppressed. In previous research we have focused on the development of this biomimetic selection architecture, and have therefore used behavioural modules that were hand-coded as algorithmic procedures. In the current article, we demonstrate the use of genetic algorithms and gradient–descent learning to automatically generate/tune some of the modules that generate the model behaviour.http://dx.doi.org/10.1080/11762320701492792 |
| spellingShingle | F. Montes-Gonzalez T. J. Prescott J. Negrete-Martinez Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control Applied Bionics and Biomechanics |
| title | Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control |
| title_full | Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control |
| title_fullStr | Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control |
| title_full_unstemmed | Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control |
| title_short | Minimizing Human Intervention in the Development of Basal Ganglia-Inspired Robot Control |
| title_sort | minimizing human intervention in the development of basal ganglia inspired robot control |
| url | http://dx.doi.org/10.1080/11762320701492792 |
| work_keys_str_mv | AT fmontesgonzalez minimizinghumaninterventioninthedevelopmentofbasalgangliainspiredrobotcontrol AT tjprescott minimizinghumaninterventioninthedevelopmentofbasalgangliainspiredrobotcontrol AT jnegretemartinez minimizinghumaninterventioninthedevelopmentofbasalgangliainspiredrobotcontrol |