The constructivist learning architecture: a model of cognitive development for robust autonomous robots
| dc.contributor.advisor | Kuipers, Benjamin | en |
| dc.contributor.advisor | Miikkulainen, Risto | en |
| dc.creator | Chaput, Harold Henry | en |
| dc.date.accessioned | 2008-08-28T21:51:07Z | en |
| dc.date.available | 2008-08-28T21:51:07Z | en |
| dc.date.issued | 2004 | en |
| dc.description | text | en |
| dc.description.abstract | Autonomous robots are used more and more in remote and inaccessible places where they cannot be easily repaired if damaged or improperly programmed. A system is needed that allows these robots to repair themselves by recovering gracefully from damage and adapting to unforeseen changes. Newborn infants employ such a system to adapt to a new and dynamic world by building a hierarchical representation of their environment. This model allows them to respond robustly to changes by falling back to an earlier stage of knowledge, rather than failing completely. A computational model that replicates these phenomena in infants would afford a mobile robot the same adaptability and robustness that infants have. This dissertation presents such a model, the Constructivist Learning Architecture (CLA), that builds a hierarchical knowledge base using a set of interconnected self-organizing learning modules. The dissertation then demonstrates that CLA (1) replicates current studies in infant cognitive development, (2) builds sensorimotor schemas for robot control, (3) learns a goal-directed task from delayed rewards, and (4) can fall back and recover gracefully from damage. CLA is a new approach to robot control that allows robots to recover from damage or adapt to unforeseen changes in the environment. CLA is also a new approach to cognitive modeling that can be used to better understand how people learn for their environment in infancy and adulthood. | |
| dc.description.department | Computer Sciences | en |
| dc.format.medium | electronic | en |
| dc.identifier | b59030136 | en |
| dc.identifier.oclc | 57587596 | en |
| dc.identifier.proqst | 3142706 | en |
| dc.identifier.uri | http://hdl.handle.net/2152/1205 | en |
| dc.language.iso | eng | en |
| dc.rights | Copyright is held by the author. Presentation of this material on the Libraries' web site by University Libraries, The University of Texas at Austin was made possible under a limited license grant from the author who has retained all copyrights in the works. | en |
| dc.subject.lcsh | Autonomous robots | en |
| dc.subject.lcsh | Robots--Error detection and recovery | en |
| dc.subject.lcsh | Robots--Control systems | en |
| dc.subject.lcsh | Cognition in infants | en |
| dc.title | The constructivist learning architecture: a model of cognitive development for robust autonomous robots | en |
| dc.type.genre | Thesis | en |
| thesis.degree.department | Computer Sciences | en |
| thesis.degree.discipline | Computer Sciences | en |
| thesis.degree.grantor | The University of Texas at Austin | en |
| thesis.degree.level | Doctoral | en |
| thesis.degree.name | Doctor of Philosophy | en |