Benchmark Agent Learning Against Open-Source Reinforcement Learning Frameworks

Summary

Evaluate Agent Learning against major open-source RL platforms.

Candidate Frameworks
Agent Lightning
AgentFly
RLlib
Stable Baselines3
CleanRL
Agent Lightning Governance Integration
Deliverables
Capability matrix
Benchmark results
Architecture comparison
Gap analysis
Acceptance Criteria
Comparison paper published
Benchmark methodology published
Recommendations documented

Start by reviewing Agent Learning and the listed open-source reinforcement learning frameworks, then define a reproducible benchmark methodology and capability matrix. Compare architecture and governance integration, and record gaps and recommendations. Done means the comparison paper, benchmark methodology, results, and recommendations are published.

Written by the indexing model from the issue text.