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作为主动推理的具身决策。

Embodied decisions as active inference.

作者信息

Priorelli Matteo, Stoianov Ivilin Peev, Pezzulo Giovanni

机构信息

Institute of Cognitive Sciences and Technologies, National Research Council, Rome, Italy.

DIAG, Sapienza University of Rome, Italy.

出版信息

PLoS Comput Biol. 2025 Jun 18;21(6):e1013180. doi: 10.1371/journal.pcbi.1013180. eCollection 2025 Jun.

Abstract

Decision-making is often conceptualized as a serial process, during which sensory evidence is accumulated for the choice alternatives until a certain threshold is reached, at which point a decision is made and an action is executed. This decide-then-act perspective has successfully explained various facets of perceptual and economic decisions in the laboratory, in which action dynamics are usually irrelevant to the choice. However, living organisms often face another class of decisions-called embodied decisions-that require selecting between potential courses of actions to be executed timely in a dynamic environment, e.g., for a lion, deciding which gazelle to chase and how fast to do so. Studies of embodied decisions reveal two aspects of goal-directed behavior in stark contrast to the serial view. First, that decision and action processes can unfold in parallel; second, that action-related components, such as the motor costs associated with selecting a particular choice alternative or required to "change mind" between choice alternatives, exert a feedback effect on the decision taken. Here, we show that these signatures of embodied decisions emerge naturally in active inference-a framework that simultaneously optimizes perception and action, according to the same (free energy minimization) imperative. We show that optimizing embodied choices requires a continuous feedback loop between motor planning (where beliefs about choice alternatives guide action dynamics) and motor inference (where action dynamics finesse beliefs about choice alternatives). Furthermore, our active inference simulations reveal the normative character of embodied decisions in ecological settings - namely, achieving an effective balance between a high accuracy and a low risk of missing valid opportunities.

摘要

决策通常被概念化为一个串行过程,在此过程中,针对各个选择选项积累感官证据,直到达到某个阈值,此时做出决策并执行行动。这种“先决策后行动”的观点成功地解释了实验室中感知和经济决策的各个方面,在实验室环境中,行动动态通常与选择无关。然而,生物体经常面临另一类决策——称为具身决策——即在动态环境中需要及时在潜在行动方案之间进行选择,例如,对于一只狮子来说,决定追逐哪只瞪羚以及以多快的速度追逐。具身决策的研究揭示了目标导向行为的两个方面,这与串行观点形成了鲜明对比。第一,决策和行动过程可以并行展开;第二,与行动相关的组成部分,例如与选择特定选择选项相关的运动成本或在选择选项之间“改变主意”所需的运动成本,会对所做出的决策产生反馈作用。在这里,我们表明具身决策的这些特征在主动推理中自然出现——这是一个根据相同的(自由能最小化)要求同时优化感知和行动的框架。我们表明,优化具身选择需要运动规划(其中关于选择选项的信念指导行动动态)和运动推理(其中行动动态完善关于选择选项的信念)之间的连续反馈回路。此外,我们的主动推理模拟揭示了生态环境中具身决策的规范性特征——即在高准确性和错过有效机会的低风险之间实现有效平衡。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/89f6/12201680/d4853461b46b/pcbi.1013180.g001.jpg

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