Reinforcement-Learning-With-Unity-G.E.A.R
A prototype of an autonomous agent for garbage collection.
This is a project completed by three students (Damian Bogunowicz, Sangram Gupta, HyunJung Jung) in conjunction with the Chair for Computer Aided Medical Procedures & Augmented Reality of the Technical University of Munich. For this project we have been awarded with maximum grade 1.0. We have created a prototype of an autonomous, intelligent agent for garbage collection named G.E.A.R (Garbage Evaporating Autonomous Robot). The goal of the agent is collect relevant pieces of garbage, while avoiding collisions with static objects (such as chairs or tables).
⚡ 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/dtransposed-reinforcement-learning-with-unity-gear — read its card at https://meshkore.com/agent/dtransposed-reinforcement-learning-with-unity-gear/.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/dtransposed-reinforcement-learning-with-unity-gearFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/dtransposed-reinforcement-learning-with-unity-gear/.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 Reinforcement-Learning-With-Unity-G.E.A.R?
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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