genpark-ppo-clipped-surrogate-loss-evaluator-skill
Proximal Policy Optimization (PPO) clipped surrogate objective calculator with KL divergence penalty
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This is 1 of 55 launches in reinforcement learning frameworks — see how it stacks up on momentum and crowding →
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Details
- External ID
- 1397464248
- Source
- GITHUB
- Company
- —
- Product
- genpark-ppo-clipped-surrogate-engine-skill
- Website domain
- github.com
- Launched
- Sept. 30, 2026
- Cohort
- —
- Upvotes
- 7
- Upvotes percentile
- 0.06
- Tags
- agent-skills, alignment, clipped-surrogate, developer-tools, mcp, optimization, policy-gradient, ppo-loss, python-standard-library, reinforcement-learning, rlhf
Enrichment
- Niche
- reinforcement learning frameworks
- Vertical
- Horizontal
- Function
- Model & infra
- Audience
- Developer
- AI stance
- AI-native
- Project type
- Hobby / open-source project
- Normalized one-liner
- ppo clipped surrogate loss calculator for rl models
- Manually corrected
- False
Could you build this?
Yes This is a mathematical function or skill calculating the standard PPO clipped surrogate loss with a KL penalty, which can be cleanly written in a few lines of PyTorch or NumPy code.
Competitors
Other products that read as similar to this one — 1020 launches clear the similarity bar, closest 8 shown.
Attention rank: #796 of 1021 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).
Launched 334 days after the earliest competitor.
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- genpark-quadratic-programming-active-set-skill · github · 2026-09-28 · 7 upvotes · similarity 0.53