Deep Reinforcement Learning Task Assignment Based on Domain Knowledge

Deep Reinforcement Learning Task Assignment Based on Domain Knowledge

Deep Reinforcement Learning (DRL) methods are inefficient in the initial strategy exploration process due to the huge state space and action space in large-scale complex scenarios. This is becoming one of the bottlenecks in their application to large-scale game adversarial scenarios. This paper prop...

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Bibliographic Details
Main Authors: Jiayi Liu, Gang Wang, Xiangke Guo, Siyuan Wang, Qiang Fu
Format: Article
Language:English
Published: IEEE 2022-01-01
Series:IEEE Access
Subjects:
Deep reinforcement learning
imitation learning
knowledge rule base
safe reinforcement learning
task assignment
Online Access:https://ieeexplore.ieee.org/document/9931113/

Internet

https://ieeexplore.ieee.org/document/9931113/

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