RICE: Breaking Through the Training Bottlenecks of Reinforcement Learning with Explanation
Deep reinforcement learning (DRL) is playing an increasingly important role in real-world
applications. However, obtaining an optimally performing DRL agent for complex tasks …
applications. However, obtaining an optimally performing DRL agent for complex tasks …
BET: Explaining Deep Reinforcement Learning through The Error-Prone Decisions
X Liu, J Zhao, W Chen, M Tan, Y Su - arXiv preprint arXiv:2401.07263, 2024 - arxiv.org
Despite the impressive capabilities of Deep Reinforcement Learning (DRL) agents in many
challenging scenarios, their black-box decision-making process significantly limits their …
challenging scenarios, their black-box decision-making process significantly limits their …
Towards an Automatic Ensemble Methodology for Explainable Reinforcement Learning
R Milani - 2024 IEEE 14th Annual Computing and …, 2024 - ieeexplore.ieee.org
Nowadays, the performances of Deep Reinforcement Learning algorithms have surpassed
human capabilities at the cost of losing transparency. For this reason, the attention has been …
human capabilities at the cost of losing transparency. For this reason, the attention has been …