GOD: Govern, Observe, and Direct - A Real-Time Control Room for Agent Societies
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Abstract (arXiv)
Generative-agent systems are easier to start than to inspect. A run can contain many agents, locations, messages, commands, and model calls, yet the operator often gets either a finished replay or raw logs. That makes it hard to ask why an agent moved, test a small intervention, or package a run for another researcher. GOD is a local-first control room for agent societies. From the same browser workflow, an operator can issue targeted questions or interventions and inspect the resulting replay state. The system combines a setup wizard, Agent Studio, Map Studio, a spatial replay interface, Ask and Intervene commands, and portable experiment, map, and agent packs. Its technical contribution is the command and artifact loop: live controls and replay evidence share the same operator command model, while package contracts separate scenario, map, and profile data from local runtime state. The public release includes hosted Smallville-style and PKU replays, the open-source repository, and downloadable packs. We evaluate this path on 15 completed run slots. Across the 14 intervention runs, 78 of 84 target-agent checks recorded the commanded destination, and 169 of 182 state answers matched a saved location or action string.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 7 of its 10 references that are in the map. First posted on arXiv 28 Aug 2026.
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7 of 10 references.
References · 7
- 2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
- 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
- 2023SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agentscited by 350
- 2025AgentSociety: Large-Scale Simulation of LLM-Driven Generative Agents Advances Understanding of Human Behaviors and Societycited by 180
- 2024AgentScope: A Flexible yet Robust Multi-Agent Platformcited by 120
- 2026Swarm Skills: A Portable, Self-Evolving Multi-Agent System Specification for Coordination Engineeringcited by 3
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