Verified claim · AI-ML · 100% confidence
Proximal Policy Optimization (PPO) introduced in paper: Proximal Policy Optimization Algorithms (Schulman et al., 2017).
Last verified 2026-05-16 · Methodology veritas-v0.1 · 00f224e1ccc158ef
Structured fields
- Subject
- Proximal Policy Optimization (PPO)
- Predicate
introduced_in_paper- Object
- Proximal Policy Optimization Algorithms (Schulman et al., 2017)
- Confidence
- 100%
- Tags
- ppo · reinforcement-learning · foundational · schulman · 2017 · openai · rlhf
Sources (2)
[1] preprint · arXiv (Schulman, Wolski, Dhariwal, Radford, Klimov) · 2017-07-20
Proximal Policy Optimization Algorithms“We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "surrogate" objective function using stochastic gradient ascent.”
[2] official blog · OpenAI · 2017-07-20
Proximal Policy Optimization
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