AI RESEARCH
From Agent Loops to Structured Graphs:A Scheduler-Theoretic Framework for LLM Agent Execution
arXiv CS.AI
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ArXi:2604.11378v1 Announce Type: new The dominant paradigm for building LLM based agents is the Agent Loop, an iterative cycle where a single language model decides what to do next by reading an ever growing context window. This paradigm has three structural weaknesses: implicit dependencies between steps, unbounded recovery loops, and mutable execution history that complicates debugging.