Name
Abstract | ||
|---|---|---|
A model for integration of low-level responses to damage, potential damage and component failure in robots is presented. This model draws on the notion of inflammation and introduces an extensible, sub-symbolic mechanism for modulating high-level behaviour using the notion of artificial inflammation. Preliminary results obtained via simulation are presented and demonstrate the potential benefits of such a scheme. Additionally the system maps the robot's physiological state-space, which is defined in terms of the levels and sources of inflammatory response. This is achieved using Kohonen's Self-Organizing Map algorithm to arrange the states experienced during the lifetime of the robot. The future use of this map for diagnosis and localization of faults and for the generation of specific high-level remediation behaviour is also discussed. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1007/11823940_27 | ICARIS |
Keywords | Field | DocType |
robot autonomy,future use,specific high-level remediation behaviour,artificial inflammation,self-organizing map algorithm,low-level response,high-level behaviour,component failure,inflammatory response,potential damage,potential benefit,artificial innate immune system,artificial immune system,innate immune system,human immune system,state space,pamps,innate immunity,robot,artificial immune systems | Artificial immune system,Computer science,Self-organization,Innate immune system,Self-organizing map,Artificial intelligence,Robot,Difference-map algorithm,Robotics | Conference |
Volume | ISSN | ISBN |
4163 | 0302-9743 | 3-540-37749-2 |
Citations | PageRank | References |
7 | 0.74 | 3 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Mark James Neal | 1 | 24 | 4.77 |
| Jan Feyereisl | 2 | 131 | 10.20 |
| Rosario Rascunà | 3 | 15 | 1.24 |
| Xiaolei Wang | 4 | 7 | 0.74 |