AgentVerse
Multi-agent framework with two distinct modes: task-solving (collaborative agents work toward a shared goal) and simulation (autonomous agents interact in an environment to study emergent social behaviour).
Description
AgentVerse is OpenBMB's multi-agent framework with a deliberate dual-mode design. In task-solving mode, several role-specialised agents coordinate to solve a single user task (similar in spirit to AutoGen GroupChat). In simulation mode, autonomous agents interact in a configured environment (e.g. a simulated software-development office, a research-paper writing committee, a virtual classroom) to study emergent collective behaviour. The framework provides shared environment abstractions (agents, environments, rules, recorders) that both modes plug into.
Solution
Environment-loop. The environment ticks; on each tick, agents perceive shared state, act (speak, use tools, move), and the environment updates. Task-solving mode runs a small fixed agent team until task termination. Simulation mode runs N autonomous agents indefinitely with no shared goal, logging interactions for offline analysis.
Primary use cases
- multi-agent task-solving with role specialisation
- social-simulation research (agent societies, emergent behaviour)
- education: configurable multi-agent classrooms and debate environments
- studying communication protocols between non-cooperative agents
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