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InstAgent: A Recursively Self-Improving Agent Operating System for Heterogeneous Robot Collaboration

InstAgent proposes a recursively self-improving (RSI) agent operating system that uses agentic behavior trees (BTs) to explicitly model capability assignment, inter-robot dependencies, and handoff checks for heterogeneous robots, and updates collaboration programs from execution feedback while preserving successful revisions for reuse in later tasks. Experiments on 20 real-world multi-robot tasks with 3 high-level models show consistent gains in task success rate, first-attempt completion rate, and execution efficiency.

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