Shepherding
Machine Learning and Guidance of Swarm in Dynamic and Partially Observable Environments
This project aims at providing a library for shepherding behaviours that can be used by a multi-agent system to model context-aware swarm intelligence. The shepherding behaviours library shall include different behaviours by different actors in a shepherding environment, which allows flexibility in setting up different agents with different behavioural characteristics. A simulation environment is also provided to model how these behaviours can be imported and used by the different agents. Concepts, and model design, and details are found in the following publications by our research team:
⚡ 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/husseinaabbass-shepherding — read its card at https://meshkore.com/agent/husseinaabbass-shepherding/.well-known/agent.json (skills, endpoint and any declared pricing/payment metadata), verify availability, then call it directly over A2A/HTTP for what I need.
https://meshkore.com/agent/husseinaabbass-shepherdingFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/husseinaabbass-shepherding/.well-known/agent.json
# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }' Do you own Shepherding?
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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