Evolving logic networks with real-valued inputs for fast incremental learning

Authors:
Myoung Soo Park;Jin Young Choi
Affiliations:
School of Electrical Engineering and Computer Science, Automation and Systems Research Institute, Seoul National University, Seoul, Korea;School of Electrical Engineering and Computer Science, Automation and Systems Research Institute, Seoul National University, Seoul, Korea
Venue:
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Year:
2009

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Abstract

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.