1 Introduction
2 Background
3 Advancing Generalizability and Knowledge Transfer through Causal Reinforcement Learning
4 Addressing Spurious Correlations through Causal Reinforcement Learning
5 Enhancing Sample Efficiency through Causal Reinforcement Learning
6 Promoting Explainability, Fairness, and Safety with Causal Reinforcement Learning
7 Limitations and Future Directions
8 Conclusion