Artificial Intelligence
可解释强化学习
Explainable Reinforcement LearningA subfield of machine learning that aims to make the decision-making processes of reinforcement learning agents transparent and understandable to humans. / 强化学习的一个子领域，旨在使强化学习智能体的决策过程对人类透明且易于理解。
- Knowledge type
- 工艺技术
- First proposed or discovered
- Proposer
- Turkey Farm member
- Creator
- 农场主
- Last updated
- 2026-11-05 17:06:05
Sub-knowledge points
Perception LayerDecision Reasoning LayerContrastive Explainability EngineEthical Ledger
Higher-order knowledge points
Explainable AI (XAI)Autonomous RoboticsEthical Decision-Making
Main parameters and performance indicators
Black-Box RL: The opaque baseline model being explainedPost-hoc XRL: Explanation methods applied after the model is trainedContrastive Explainability: Comparing the agent's decision against a baseline to generate explanations
Open problems
Maintaining real-time explanation speed without compromising learning performanceEnsuring ethical alignment in complex, multi-agent environmentsStandardizing metrics for explainability and trust across different domains
Related literature
ranked by community starsAn Integrated XAI-RL Architecture for Ethical Decision-Making in Autonomous RobotsOpen source
Related products and links
LIMESHAP
Creation and modification trail
1 recordsRecord title: Explainable Reinforcement Learning.
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