TY - GEN
T1 - Constructivism-Inspired Meta-Knowledge Learning and Reuse
AU - Peng, Cheng
AU - Wen, Zaidao
AU - Pan, Quan
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Efficient continual learning of humans is enabled by interactions of a series of learning mechanisms and human memory system. Constructivism is a theory in education that proposes learners construct knowledge from their experiences, assimilation and accommodation are key to this process. Also, research shows knowledge in human memory system is represented as a high-dimensional and sparse vector. Motivated by these, in our paper, we propose a continual feature learning method based on constructivisim and memory system. We divide continual feature learning into two stages. In assimilation stage, assimilation model captures knowledge that cannot be represented by meta-knowledge in knowledge base and update the knowledge base according to new knowledge. Furthermore, in accommodation stage, accommodation model updates its learning ability based on new tasks and new knowledge base, ensuring the continual feature learning of new tasks without forgetting previous knowledge. Experimental results show our proposed method can further alleviate the forgetting effect of the model.
AB - Efficient continual learning of humans is enabled by interactions of a series of learning mechanisms and human memory system. Constructivism is a theory in education that proposes learners construct knowledge from their experiences, assimilation and accommodation are key to this process. Also, research shows knowledge in human memory system is represented as a high-dimensional and sparse vector. Motivated by these, in our paper, we propose a continual feature learning method based on constructivisim and memory system. We divide continual feature learning into two stages. In assimilation stage, assimilation model captures knowledge that cannot be represented by meta-knowledge in knowledge base and update the knowledge base according to new knowledge. Furthermore, in accommodation stage, accommodation model updates its learning ability based on new tasks and new knowledge base, ensuring the continual feature learning of new tasks without forgetting previous knowledge. Experimental results show our proposed method can further alleviate the forgetting effect of the model.
KW - constructivism learning
KW - continual feature learning
KW - knowledge base
KW - meta-knowledge
UR - http://www.scopus.com/inward/record.url?scp=85189290201&partnerID=8YFLogxK
U2 - 10.1109/CAC59555.2023.10450325
DO - 10.1109/CAC59555.2023.10450325
M3 - 会议稿件
AN - SCOPUS:85189290201
T3 - Proceedings - 2023 China Automation Congress, CAC 2023
SP - 2492
EP - 2497
BT - Proceedings - 2023 China Automation Congress, CAC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 China Automation Congress, CAC 2023
Y2 - 17 November 2023 through 19 November 2023
ER -