Towards Explaining Sequences of Actions in Multi-Agent Deep Reinforcement Learning Models
Although Multi-agent Deep Reinforcement Learning (MADRL) has shown promising results in solving complex real-world problems, the applicability and reliability of MADRL models are often limited by a lack of understanding of their inner workings for explaining the decisions made. To address this issue...
محفوظ في:
المؤلفون الرئيسيون: | KHAING, Phyo Wai, GENG, Minghong, SUBAGDJA, Budhitama, PATERIA, Shubham, TAN, Ah-hwee |
---|---|
التنسيق: | text |
اللغة: | English |
منشور في: |
Institutional Knowledge at Singapore Management University
2023
|
الموضوعات: | |
الوصول للمادة أونلاين: | https://ink.library.smu.edu.sg/sis_research/8076 https://ink.library.smu.edu.sg/context/sis_research/article/9079/viewcontent/p2325.pdf |
الوسوم: |
إضافة وسم
لا توجد وسوم, كن أول من يضع وسما على هذه التسجيلة!
|
المؤسسة: | Singapore Management University |
اللغة: | English |
مواد مشابهة
-
Explaining Sequences of Actions in Multi-agent Deep Reinforcement Learning Models
بواسطة: KHAING, Phyo Wai, وآخرون
منشور في: (2024) -
Benchmarking MARL on Long Horizon Sequential Multi-Objective Tasks
بواسطة: GENG, Minghong, وآخرون
منشور في: (2024) -
HiSOMA: A hierarchical multi-agent model integrating self-organizing neural networks with multi-agent deep reinforcement learning
بواسطة: GENG, Minghong, وآخرون
منشور في: (2024) -
Reinforced Negative Sampling over Knowledge Graph for Recommendation
بواسطة: Xiang Wang, وآخرون
منشور في: (2020) -
End-to-end deep reinforcement learning for multi-agent collaborative exploration
بواسطة: CHEN, Zichen, وآخرون
منشور في: (2019)