Name
Abstract | ||
|---|---|---|
Starting with a neural model for classical conditioning we have developed a system for robot control that is completely self-organizing. Instead of relying on predefined control rules the system will develop adapted control by interacting with its environment. We have tested this model in navigation tasks. Our results demonstrate that the level at which control models are normally defined seems to emerge out of the neural level which implements our control architecture. |
Year | DOI | Venue |
|---|---|---|
1992 | 10.1016/0921-8890(92)90054-3 | Robotics and Autonomous Systems |
Keywords | Field | DocType |
Mobile robots,Autonomous agents,Sensor-based control,Neuro-computing,Artificial intelligence,Classical conditioning,Emergence | Robot control,Autonomous agent,Computer science,Simulation,Real-time Control System,Artificial intelligence,Autonomous system (mathematics),Adaptive control,Artificial neural network,Mobile robot,Robotics | Journal |
Volume | Issue | ISSN |
9 | 3 | Robotics and Autonomous Systems |
Citations | PageRank | References |
48 | 13.21 | 13 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paul F. M. J. Verschure | 1 | 188 | 29.61 |
| Ben J.A. Kröse | 2 | 825 | 63.93 |
| Rolf Pfeifer | 3 | 1398 | 161.88 |