openai/evolution-strategies-starter
Code for the paper "Evolution Strategies as a Scalable Alternative to Reinforcement Learning" observed · 2026-08-28
Health v2 · maintenance only
10/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases archived
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 3449
- days_rel: n/a
- days_push: 2498
- n_releases_24m: 0
Adoption not part of the score
1635 stars · 279 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A distributed Python implementation of Evolution Strategies (ES) from OpenAI's paper 'Evolution Strategies as a Scalable Alternative to Reinforcement Learning'. It uses a master-worker architecture designed to scale to over a thousand parallel workers on AWS EC2, including spot instances.
Use cases
- run distributed evolution strategies for reinforcement learning
- train RL policies on MuJoCo humanoid tasks
- scale black-box optimization across many CPUs
- reproduce results from the ES paper
- run RL experiments on AWS spot instances
When to choose
- you want to experiment with evolution strategies as an RL alternative
- you need a reference implementation of the scalable ES algorithm
- you have AWS infrastructure and want massively parallel black-box optimization
When to avoid
- you need maintained or updated code (the repo is archived)
- you want a modern RL framework with GPU support
- you lack an AWS account or Mujoco license
Facets
library · maturity abandoned
machine-learning reinforcement-learning concurrency machine-learning artificial-intelligence cloud-computing python cloud evolution-strategies distributed-training research-code aws mujoco black-box-optimization linux
6 sources
- readme: https://github.com/openai/evolution-strategies-starter · fetched 2026-08-28 · a1b192a2ff2d
- homepage: https://arxiv.org/abs/1703.03864 · fetched 2026-08-29 · e193ed980e93
- site_page: https://info.arxiv.org/about/donate.html · fetched 2026-08-29 · cca9c3a11c56
- site_page: https://info.arxiv.org/about/ourmembers.html · fetched 2026-08-29 · 47cbc55ff1de
- site_page: https://info.arxiv.org/about · fetched 2026-08-29 · a1f16f915a9a
- site_page: https://info.arxiv.org/labs/index.html · fetched 2026-08-29 · b14a8d05a0ec
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| openai/evolution-strategies-starter | main | 10 |
For agents
markdown · JSON · MCP: product_card(name="openai/evolution-strategies-starter")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem