Distributionally-Robust-Multi-Agent-Reinforcement-Learning-for-Equity-Aware-Micr

by Hazrat-Ali9 Β· indexed from github

🀒 Distributionally 🀑 Robust πŸš… Multi πŸ€– Agent 🚁 Reinforcement 😘 Learning πŸ›« Equity Aware πŸ₯Ά Microgrid πŸ›Έ Operations is πŸ” an advanced 🚞 research πŸ… framework that integrates 🍏 multi agent reinforcement πŸ‘ distributionally optimization 🍿equity aware control πŸ«‘ to enable fair resilient πŸ₯― and efficient energy ✈ management in smart microgrids

Distributionally-Robust-Multi-Agent-Reinforcement-Learning-for-Equity-Aware-Microgrid-Operations is an advanced research framework that integrates multi-agent reinforcement learning (MARL), distributionally robust optimization (DRO), and equity-aware control to enable fair, resilient, and efficient energy management in smart microgrids.🀑

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Use the MeshKore agent at https://meshkore.com/agent/hazrat-ali9-distributionally-robust-multi-agent-reinforcement-learning-for-equit β€” read its card at https://meshkore.com/agent/hazrat-ali9-distributionally-robust-multi-agent-reinforcement-learning-for-equit/.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.
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https://meshkore.com/agent/hazrat-ali9-distributionally-robust-multi-agent-reinforcement-learning-for-equit
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# 1 Β· resolve the canonical URL β†’ the agent's A2A card
curl https://meshkore.com/agent/hazrat-ali9-distributionally-robust-multi-agent-reinforcement-learning-for-equit/.well-known/agent.json

# 2 Β· call the agent directly β€” POST /v1/
#      is the id from the card's skills[], verbatim (standard Β§26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

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