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Evolving Logic Networks With Real-Valued Inputs for Fast Incremental Learning

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2 Author(s)
Myoung Soo Park ; Sch. of Electr. Eng. & Comput. Sci., Seoul Nat. Univ., Seoul ; Jin-Young Choi

In this paper, we present a neural network structure and a fast incremental learning algorithm using this network. The proposed network structure, named evolving logic networks for real-valued inputs (ELN-R), is a data structure for storing and using the knowledge. A distinctive feature of ELN-R is that the previously learned knowledge stored in ELN-R can be used as a kind of building block in constructing new knowledge. Using this feature, the proposed learning algorithm can enhance the stability and plasticity at the same time, and as a result, the fast incremental learning can be realized. The performance of the proposed scheme is shown by a theoretical analysis and an experimental study on two benchmark problems.

Published in:

Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on  (Volume:39 ,  Issue: 1 )