Convergence Analysis of Federated SARSA with Local Training
Published:Dec 19, 2025 15:23
•1 min read
•ArXiv
Analysis
This research paper explores the convergence properties of Federated SARSA, a reinforcement learning algorithm suitable for distributed training. The focus on heterogeneous agents and local training adds complexity and practical relevance to the theoretical analysis.
Key Takeaways
- •Focuses on convergence guarantees for Federated SARSA in a distributed setting.
- •Considers heterogeneous agents, which is more realistic for real-world scenarios.
- •Investigates the impact of local training on the overall convergence behavior.
Reference
“The paper investigates Federated SARSA with local training.”