Conference Proceedings

An Idiotypic Immune Network as a Short-Term Learning Architecture for Mobile Robots

Amanda Whitbrook, Uwe Aickelin, Jonathan M Garibaldi

Proceedings of the 7th International Conference on Artificial Immune Systems (ICARIS 2008), LNCS 5132, Phuket, Thailand | Springer Verlag | Published : 2008


A combined Short-Term Learning (STL) and Long-Term Learning (LTL) approach to solving mobile robot navigation problems is presented and tested in both real and simulated environments. The LTL consists of rapid simulations that use a Genetic Algorithm to derive diverse sets of behaviours. These sets are then transferred to an idiotypic Artificial Immune System (AIS), which forms the STL phase, and the system is said to be seeded. The combined LTL-STL approach is compared with using STL only, and with using a hand-designed controller. In addition, the STL phase is tested when the idiotypic mechanism is turned off. The results provide substantial evidence that the best option is the seeded idio..

View full abstract

University of Melbourne Researchers