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How Multi-Agent AI Simulations Keep a Shared World State
What actually holds a simulated world together when multiple AI agents act inside it? This episode opens the repos on three frameworks that answer the question completely differently. Concordia from Google DeepMind makes world state a first-class Game Master component — a plain Python dict whose contents are authored by the model at every step, with a SQLite/Postgres storage protocol that ships as an interface but not an implementation. Generative Agents goes the other way: a deterministic tile grid in CSV files, per-agent JSON scratch files, and a memory system with a 0.995 recency decay…
The skinny
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