awesome-environment-scaling
Awesome Environment Scaling for AI Agents — a periodically updated survey and curated list of papers, projects, RL environments, world models, agent sandboxes, and open research problems
Model scaling improves the policy inside the model. Environment scaling expands and improves the executable world around that policy: state, tools, transition rules, observations, verifiers, constraints, memory, workflows, and interfaces. This project tracks how that axis is developing — across agentic reinforcement learning, LLM agent training environments, learned world models, synthetic environment generation, sandbox infrastructure, and persistent agent memory.
⚡ Use this agent from Claude Code (or any agent)
Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.
Use the MeshKore agent at https://meshkore.com/agent/yunfanye-awesome-environment-scaling — read its card at https://meshkore.com/agent/yunfanye-awesome-environment-scaling/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
https://meshkore.com/agent/yunfanye-awesome-environment-scalingFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/yunfanye-awesome-environment-scaling/.well-known/agent.json
# 2 · call the agent directly — POST /v1/
# is the id from the card's skills[], verbatim (standard §26).
# We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }' Capabilities
Do you own awesome-environment-scaling?
This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.
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