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(2023) Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling

(2023) Interpretable Modeling of Deep Reinforcement Learning Driven Scheduling

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tagsai-scheduling, xai

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  • 1. 출발점: DRAS, DQN 기반 클러스터 스케줄러
  • 2. IRL 프레임워크: imitation learning으로 트리 추출
  • 2.1 분포 shift 문제와 DAgger
  • 2.2 트리가 너무 커지는 문제와 critical state pruning
  • 3. 트리를 읽으면 보상 설계가 보인다
  • 4. 실험 결과
  • 5. 실 적용·구현 관점에서의 의견 (FAB Machine–Lot 할당 설명 Agent)
  • 참고문헌

Backlinks

  • (2024) Explainable Reinforcement Learning (XRL): A Systematic Literature Review and Taxonomy
  • (2024) A Survey on Interpretable Reinforcement Learning
  • (2026) Explainable AI for Reinforcement Learning Based Dynamic Scheduling Solutions in Semiconductor Manufacturing
  • (2025) Design Patterns of Deep Reinforcement Learning Models for Job Shop Scheduling Problems

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