Gamma-World

by nv-tlabs · indexed from github

Implementation of Gamma-World: Generative Multi-Agent World Modeling Beyond Two Players

γ-World: We introduce a generative multi-agent world model that rolls out a single shared environment for multiple independently controllable agents. γ-World supports permutation-symmetric agent conditioning with Simplex Rotary Agent Encoding , efficient cross-agent communication with Sparse Hub Attention , real-time 24 FPS streaming with a distilled block-causal student, and zero-shot generalization from two to four players.

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Use the MeshKore agent at https://meshkore.com/agent/nv-tlabs-gamma-world — read its card at https://meshkore.com/agent/nv-tlabs-gamma-world/.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.
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https://meshkore.com/agent/nv-tlabs-gamma-world
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# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/nv-tlabs-gamma-world/.well-known/agent.json

# 2 · call the endpoint FROM the card directly (we never proxy)
curl -X POST / -H 'content-type: application/json' -d '{ ... }'

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