arXiv：cs.AI· St John Grimbly, Nicolas Kuske, Evert A. Boonstra, Charel van Hoof, Rowan Hodson, Benjamin Rosman, Ryan Smith, Mark Solms, Jonathan P. Shock·· 6 小时前
主动推理中内感受优先化的两条路径：解离似然精度与偏好重加权
Two Routes to Interoceptive Prioritisation: Dissociating Likelihood Precision and Preference Reweighting in Active Inference
AI 导读
主动推理框架下，智能体可通过提高需求信息的精度或增强偏好来应对紧急生理需求。在含三种致命需求的觅食网格世界实验中，精度提升锐化了内感受后验并改善生存，偏好重加权则使身体状态远离致命边界但学到的模型覆盖需求层级更少。72 个额外布局实验未能验证偏好重加权在困难布局上的预期收益，但两种干预均提升了平均生存率且交互为正。
正文
Abstract:An embodied agent must prioritise among competing bodily needs. In active inference, it can respond to an urgent need by increasing the precision of information about that need or by increasing its preference for outcomes that relieve it. We compare these two interventions, separately and together, in a foraging gridworld with three lethal needs, and ask how each changes survival, perception and the body model the agent learns. Precision sharpens interoceptive posteriors and improves survival. Preference reweighting keeps bodily states further from their lethal boundaries and changes the states from which the agent learns, so its learned model covers fewer need levels, with lower quality across all levels but slightly higher quality on the levels it visits. An experiment on 72 further layouts does not establish the predicted preference benefit on difficult layouts, but both interventions improve average survival there and their interaction is positive. Survival alone therefore gives an incomplete account of how a model prioritises needs and learns about its body.
| Comments: | Accepted at IWAI 2026, forthcoming in the Springer proceedings. 17 pages: the 13-page camera-ready paper, reproduced without alteration apart from one typographical fix, followed by 4 pages of supplementary material. Code: this https URL |
| Subjects: | Artificial Intelligence (cs.AI); Neurons and Cognition (q-bio.NC) |
| Cite as: | arXiv:2610.18617 [cs.AI] |
| (or arXiv:2610.18617v1 [cs.AI] for this version) | |
| https://doi.org/10.48550/arXiv.2610.18617 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: St John Grimbly [view email]
[v1]
Tue, 13 Oct 2026 16:01:02 UTC (469 KB)
来源：arXiv：cs.AI · arxiv.org