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多轮信号博弈中的主动迭代社会推理

Active Iterative Social Inference in Multi-Trial Signaling Games.

作者信息

Achimova Asya, Scontras Gregory, Eisemann Ella, Butz Martin V

机构信息

Research Training Group 1808 "Ambiguity: Production and Perception", University of Tübingen, Tübingen, Germany.

Department of General and Computational Linguistics, University of Tübingen, Tübingen, Germany.

出版信息

Open Mind (Camb). 2023 Apr 5;7:111-129. doi: 10.1162/opmi_a_00074. eCollection 2023.

Abstract

Human behavioral choices can reveal intrinsic and extrinsic decision-influencing factors. We investigate the inference of choice priors in situations of referential ambiguity. In particular, we use the scenario of signaling games and investigate to which extent study participants profit from actively engaging in the task. Previous work has revealed that speakers are able to infer listeners' choice priors upon observing ambiguity resolution. However, it was also shown that only a small group of participants was able to strategically construct ambiguous situations to create learning opportunities. This paper sets to address how prior inference unfolds in more complex learning scenarios. In Experiment 1, we examine whether participants accumulate evidence about inferred choice priors across a series of four consecutive trials. Despite the intuitive simplicity of the task, information integration turns out to be only partially successful. Integration errors result from a variety of sources, including transitivity failure and recency bias. In Experiment 2, we investigate how the ability to actively construct learning scenarios affects the success of prior inference and whether the iterative settings improve the ability to choose utterances strategically. The results suggest that full task engagement and explicit access to the reasoning pipeline facilitates the invocation of optimal utterance choices as well as the accurate inference of listeners' choice priors.

摘要

人类的行为选择能够揭示内在和外在的决策影响因素。我们研究了在参考模糊情境下对选择先验的推断。具体而言,我们采用信号博弈的场景,并研究研究参与者在积极参与任务的过程中能在多大程度上从中获益。先前的研究表明,说话者在观察到模糊性的解决后能够推断出听众的选择先验。然而,研究还表明,只有一小部分参与者能够策略性地构建模糊情境以创造学习机会。本文旨在探讨在更复杂的学习场景中先验推断是如何展开的。在实验1中,我们检验参与者是否会在连续的四个试验系列中积累关于推断出的选择先验的证据。尽管该任务直观简单,但信息整合结果却只是部分成功。整合错误源于多种来源,包括传递性失败和近因偏差。在实验2中,我们研究积极构建学习场景的能力如何影响先验推断的成功,以及迭代设置是否能提高策略性选择话语的能力。结果表明,全身心投入任务并明确访问推理流程有助于调用最优话语选择以及准确推断听众的选择先验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/ba29/10320816/2f6f81a02f2b/opmi-07-111-g001.jpg

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