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RecursiveMAS

by RecursiveMAS

Framework for recursive task-decomposing multi-agent systems

Python
Updated Jun 29, 2026
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How It Works

Implements Recursive Multi-Agent Systems to coordinate agents that spawn and reason about sub-agents recursively. Uses a recursive task-decomposition pattern where agents create specialist sub-agents, aggregate their results, and iterate until a termination condition. Notable for separating reasoning layers and supporting latent collaboration strategies for scale and composability. See the A2A Protocol Pattern for related coordination patterns.

The Value Proposition

As agents become more autonomous and delegate subtasks, understanding how recursive delegation affects reliability and failure modes is critical. RecursiveMAS provides a concrete architecture to observe how task decomposition, recursion depth, and agent chaining influence outcomes and error propagation. That makes it valuable for teams designing trust policies, reputation signals, and evaluation harnesses around agent-to-agent interactions. Consider exploring failure modes like Coordination Deadlock to anticipate and mitigate risks.

Target Use Cases

Researchers and engineers building or prototyping agent pipelines that use recursive delegation and need to study interaction/ failure patterns. This approach aligns with established patterns such as Tree of Thoughts Pattern and supports robust design through Defense in Depth Pattern.

Applications

  • Decomposing complex tasks into recursive sub-agents to evaluate end-to-end reliability
  • Experimenting with recursion depth and aggregation strategies to find failure modes
  • Tracing how sub-agent outputs influence parent decisions for reputation and trust signals
Topics
agent-collaborationlatent-collaborationmulti-agent-systemsreasoning-agentrecursive-algorithmscaling-algorithms
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Keywords
multi-agent orchestrationmulti-agent trustagent delegationagent failure modes