【专题研究】Agent Debate是当前备受关注的重要议题。本报告综合多方权威数据，深入剖析行业现状与未来走向。
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综合多方信息来看，instructions="""When generating reports:
值得注意的是，Hard warm-start with regret-magnitude weighting. Policy averaging is fully delayed until iteration 500. Regret accumulation proceeds normally until then. Once averaging starts, policies are weighted by both time and immediate regret size—emphasizing high-information rounds in the average strategy. The 500-iteration delay was generated by the LLM without prior knowledge of the 1000-iteration evaluation limit.
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面对Agent Debate带来的机遇与挑战，业内专家普遍建议采取审慎而积极的应对策略。本文的分析仅供参考，具体决策请结合实际情况进行综合判断。