<<Best Presentation Award in WCCI-IJCNN 2006>>
(Session: Intelligent Control Applications, Conference on July. 16-21,
2006)
Title:
Developmental Learning Based on Coherent Neural
Networks with Behavioral Mode Tuning by Carrier-Frequency Modulation
Authors:
Akira Hirose, Yasufumi Asano, Toshihiko Hamano
Abstract:
We analyze the developmental-learning dynamics with
which a motion-control system learns multiple tasks similar to each other or
advanced ones incrementally and efficiently by tuning its behavioral mode. The
system is based on a coherent neural network whose carrier frequency functions
as a mode-tuning parameter. We consider two tasks related to bicycle riding,
i.e., to ride as temporally long as the system can (Task 1) and to ride as far
as possible in a certain direction (Task 2) which is an advanced one. We
compare developmental learning to learn Task 2 after Task 1 with the direct
learning of Task 2. We also examine the effect of the mode tuning by comparing
variable-mode learning (VML), where the carrier frequency is set free to move,
with fixed-mode learning (FML), where the frequency is unchanged. We find that
VML developmental learning results in the most efficient learning among the
possible combinations.