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COLLATOR: Compositional Multi-Agent Orchestration with Counterfactual Reinforcement Learning
Large language models (LLMs) provide a flexible foundation for multi-agent systems, but their effectiveness and computational cost depend critically on orchestration design. Across different tasks, role design, capacity assignment, and dependency construction jointly affect both solution quality and
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