Multi_Agent_Soft_Actor_Critic
A Pytorch Implementation of Multi Agent Soft Actor Critic
The environment consists of multiple agents where the task of the agent hit the ball and keep it in the air without allowing it to fall on the ground. The current state of the environment is represented by 24 dimensional feature vector which conist the position of the ball and speed of the ball Action space is continous and thus it represent by a vector with 2 numbers, corresponding to position of the bat ranging between -1 and 1 in each dimension. A reward of +0.1 is provided for time the agent's hits the ball and -0.1 if the agent miss it or shoots the ball away from the court.
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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/adithya-subramanian-multiagentsoftactorcritic — read its card at https://meshkore.com/agent/adithya-subramanian-multiagentsoftactorcritic/.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/adithya-subramanian-multiagentsoftactorcriticFor machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/adithya-subramanian-multiagentsoftactorcritic/.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 Multi_Agent_Soft_Actor_Critic?
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