[3Win5] Poster session 3

[3Win5-86] Developmental Approach towards Mitigating Catastrophic Forgetting

〇HANJU LEE¹, Hiromichi Hagihara², Yasuhiro Kanakogi² (1.DENSO, 2.The University of Osaka)

Keywords:Catastrophic forgetting, Developmental Cognitive Science

Artificial Neural Networks (ANN) involve significant computational costs during updates due to catastrophic forgetting, where new learning overwrites existing knowledge, necessitating the relearning of all data. Despite various attempts to address this issue, no method has yet reached a practical level. Brain-inspired methods are particularly noteworthy, as biological neural networks do not suffer from catastrophic forgetting. Researchers have attempted to mimic the brain's memory mechanisms, achieving state-of-the-art performance in some cases. However, the developmental aspects of the memory mechanisms have not been sufficiently considered. By examining the brain's functional developmental sequence and the stimuli necessary for development, we aim to gain insights into suppressing catastrophic forgetting. This paper introduces the experimental setup and shares preliminary results.