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Schulman and colleagues: proximal policy optimization

Contribution grade

Reinforcement learning · Policy-gradient algorithms

Reference score115,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

A relatively simple policy-update method achieved favorable benchmark tradeoffs.

Scientific scope

2017 five-author technical paper and its benchmarks; later PPO variants and deployments excluded.

Evidence

The linked sources identify this contribution and its scope. WRS has not independently reconstructed the scientific claims. The record is the 2017 five-author technical paper and its reported benchmarks. PPO variants, later theory and broad deployment claims are separate.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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