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통찰 - Causal Imitation Learning
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
Causal discovery is utilized in imitation learning to identify causal features for domain generalization, leading to the DIGIC framework.
DIGIC: Domain Generalizable Imitation Learning by Causal Discovery
デモンストレーションデータ分布から因果関係を直接特定し、ドメイン汎用の模倣学習を実現するための新しいフレームワークであるDIGICを導入します。
Domain Generalizable Imitation Learning by Causal Discovery
The author proposes the DIGIC framework to identify causal features directly from demonstration data distribution for domain generalization in imitation learning.