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genpark-ppo-clipped-surrogate-engine-skill

Proximal Policy Optimization (PPO) clipped surrogate objective engine maintaining stable trust-region policy updates and bounding gradient divergence.

Details

External ID
1363397287
Source
GITHUB
Company
—
Product
genpark-ppo-clipped-surrogate-engine-skill
Website domain
github.com
Launched
Sept. 10, 2026
Cohort
—
Upvotes
7
Upvotes percentile
0.05976172175249808
Tags
actor-critic, agentic-ai, genpark-skill, policy-gradient, ppo, reinforcement-learning
Fetched at
Sept. 14, 2026, 1:02 a.m.
Updated at
Sept. 14, 2026, 1:02 a.m.

Enrichment

Theme
specialized AI models and agent reasoning tools
Vertical
Horizontal
Function
Model & infra
Audience
Developer
AI stance
AI-native
Project type
Hobby / open-source project
Normalized one-liner
ppo clipped surrogate objective engine for reinforcement learning
Manually corrected
False

Could you build this?

Yes The clipped surrogate objective for PPO is standard PyTorch/TensorFlow code easily synthesized or imported from libraries like CleanRL or Stable-Baselines3.

Competitors

Other products that read as similar to this one — 306 launches clear the similarity bar, closest 8 shown.

Attention rank: #138 of 307 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 255 days after the earliest competitor.

Other launches for this product

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