human_drone_SC
[ICDE 2022] Human-Drone Collaborative Spatial Crowdsourcing by Memory-Augmented Distributed Multi-Agent Deep Reinforcement Learning
FD-MAPPO (Cubic Map) is a novel deep reinforcement learning (DRL) framework for human-drone collaborative SC tasks. It consists of a fully decentralized MADRL framework, called FD-MAPPO, as a novel multi-actor-multi-learner architecture without any centralized control module based on PPO. It also contains a novel memory structure, called Cubic Map, to enable novel sparse cubic writing and contextual attentive reading operations.
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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/bit-mcs-humandronesc — read its card at https://meshkore.com/agent/bit-mcs-humandronesc/.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/bit-mcs-humandronescFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/bit-mcs-humandronesc/.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 human_drone_SC?
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