标题： 多思维思考：使用大型语言模型进行多角度问题解决 显示英文标题

标题： Thinking with Many Minds: Using Large Language Models for Multi-Perspective Problem-Solving

摘要： 复杂问题解决需要认知灵活性——即在保持不同观点独特性的同时，能够接受多种视角的能力。 这种灵活性在单个个体内部复制了“群体智慧”，使他们能够“用许多思维进行思考”。 虽然心理模拟可以实现想象中的权衡，但认知限制会降低其效果。 我们提出了一种基于大型语言模型（LLM）的方法——合成权衡，该方法模拟体现不同视角的代理之间的对话，作为解决方案。 使用一个定制的基于GPT的模型，我们展示了其优势：在不造成认知退化的情况下同时处理多个观点，平行探索各种观点，并精确控制观点的合成。 通过将权衡过程外部化，并在并行搜索和整合之间分配认知劳动，合成权衡超越了心理模拟的局限性。 这种方法在战略规划、政策制定和冲突解决方面显示出前景。 显示英文摘要

摘要： Complex problem-solving requires cognitive flexibility--the capacity to entertain multiple perspectives while preserving their distinctiveness. This flexibility replicates the "wisdom of crowds" within a single individual, allowing them to "think with many minds." While mental simulation enables imagined deliberation, cognitive constraints limit its effectiveness. We propose synthetic deliberation, a Large Language Model (LLM)-based method that simulates discourse between agents embodying diverse perspectives, as a solution. Using a custom GPT-based model, we showcase its benefits: concurrent processing of multiple viewpoints without cognitive degradation, parallel exploration of perspectives, and precise control over viewpoint synthesis. By externalizing the deliberative process and distributing cognitive labor between parallel search and integration, synthetic deliberation transcends mental simulation's limitations. This approach shows promise for strategic planning, policymaking, and conflict resolution.