HACO
[ICLR 2022] Official implementation of paper: Efficient Learning of Safe Driving Policy via Human-AI Copilot Optimization
HACO is designed for teaching AI to learn a generalizable autonomous driving policy efficiently and safely. Supported by MetaDrive, the concrete goal of driving tasks is to drive the vehicle to the destination with as fewer collision as possible. Also, to prevent driving out of the road which will terminate the episode, please follow the yellow checkpoints indicating navigation information when you are training HACO.
⚡ 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/decisionforce-haco — read its card at https://meshkore.com/agent/decisionforce-haco/.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/decisionforce-hacoFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/decisionforce-haco/.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 '{ ... }' Do you own HACO?
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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