arXiv:2604.19791cs.AI2026-04被引 1

将态度变化的三种经典理论转化为可运行的模拟系统,揭示其背后的隐性假设。

Stabilising Generative Models of Attitude Change

论文配图:Stabilising Generative Models of Attitude Change
图 1 · 摘自论文原文
  • 用预测模式补全机制实现认知失调、自我一致性等理论的决策逻辑
  • 在经典心理学实验中复现了已知行为模式,但需手动调优才能稳定
  • 揭示了理论未明说的社会生态与表征依赖,适合认知科学与社会模拟研究者

态度变化——个体调整评价立场的过程——已有若干有影响力的竞争性言语理论。这些理论常作为机制草图:概念丰富,但缺乏技术细节和操作约束,无法直接运行。本文提出一种基于生成代理的建模流程,使用Concordia仿真库将这些草图转化为可执行的代理-环境模拟。在Concordia中,代理通过自然语言字符串的预测模式补全来运作:从包含过去记忆和当前观察的前缀生成描述其意图的动作后缀。我们将认知失调(Festinger, 1957)、自我一致性(Aronson, 1969)和自我归因(Bem, 1972)理论分别转化为独特的决策逻辑,通过特定推理步骤处理前缀。我们在经典心理学实验中评估这些实现,结果生成的行为模式与原始实证文献一致。然而,实现稳定再现需要解决言语理论的内在不确定性,以及现代语言先验与历史实验假设之间的冲突。我们记录了这一手动迭代模型‘稳定化’过程所暴露的具体操作与社会生态依赖关系,这些在原始言语理论中基本未被记录。最终我们认为,这种手动稳定化过程本身应被视为方法论的核心部分,用于澄清生成典型效应所需的情境与表征承诺。

原文摘要 · Abstract (English)

Attitude change - the process by which individuals revise their evaluative stances - has been explained by a set of influential but competing verbal theories. These accounts often function as mechanism sketches: rich in conceptual detail, yet lacking the technical specifications and operational constraints required to run as executable systems. We present a generative actor-based modelling workflow for "rendering" these sketches as runnable actor - environment simulations using the Concordia simulation library. In Concordia, actors operate by predictive pattern completion: an operation on natural language strings that generates a suffix which describes the actor's intended action from a prefix containing memories of their past and observations of the present. We render the theories of cognitive dissonance (Festinger 1957), self-consistency (Aronson 1969), and self-perception (Bem 1972) as distinct decision logics that populate and process the prefix through theory-specific sequences of reasoning steps. We evaluate these implementations across classic psychological experiments. Our implementations generate behavioural patterns consistent with known results from the original empirical literature. However, we find that achieving stable reproduction requires resolving the inherent underdetermination of the verbal accounts and the conflicts between modern linguistic priors and historical experimental assumptions. We document how this manual process of iterative model "stabilisation" surfaces specific operational and socio-ecological dependencies that were largely undocumented in the original verbal accounts. Ultimately, we argue that the manual stabilisation process itself should be regarded as a core part of the methodology functioning to clarify situational and representational commitments needed to generate characteristic effects.

态度变化生成模型社会模拟认知科学

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