Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks.
We illustrate the ability of a fixed-weight neural network, trained with Kalman filter methods, to perform tasks that are usually entrusted to an explicitly adaptive system. Following a simple example, we demonstrate that such a network can be trained to exhibit input-output behavior that depends on which of two conditioning tasks was performed a substantial number of time steps in the past. This behavior can also be made to survive an intervening interference task.
Feldkamp
Lee A
LA
Research and Advanced Engineering, Ford Motor Company, Dearborn, MI, USA.
Prokhorov
Danil V
DV
Feldkamp
Timothy M
TM
D000223:Adaptation, Psychological / Q000502:physiology; D003213:Conditioning, Psychological / Q000502:physiology; D016571:Neural Networks, Computer