Comprehensive Review of Causal Reinforcement Learning: Surveying Algorithms and Applications
Analysis
This ArXiv article provides a valuable contribution by surveying and categorizing causal reinforcement learning (CRL) algorithms and their applications. It offers a structured approach to a rapidly evolving field, potentially accelerating research and facilitating practical implementations of CRL.
Key Takeaways
- •Presents a comprehensive survey of existing causal reinforcement learning techniques.
- •Offers a taxonomy for categorizing different CRL algorithms.
- •Highlights potential applications of CRL, suggesting future research directions.
Reference / Citation
View Original"The article is a survey of the field, encompassing algorithms and applications."