arXiv cs.AI· Marco Gabriele Fedozzi, Yukie Nagai, Francesco Rea, Alessandra Sciutti·· 12 小时前AI 评分18
条件神经过程如何实现动作模仿中的自监督目标发现
Conditional Neural Processes for Self-Supervised Goal Discovery in Action Imitation
AI 导读
研究评估条件神经过程（Conditional Neural Processes）能否自主学习对动作潜在目标有信息量的动作表征。在隐空间加入注意力机制后，模型能在观察动作序列的早期阶段形成稳健的目标表征，被视为有潜力的机器人自监督通用学习器。该工作发表于 IROS2023 世界模型与认知机器人预测编码研讨会海报环节。
正文 · 原文
Abstract:Inspired by infants' ability to learn novel tasks by imitating others, in this work we evaluate to what extent Conditional Neural Processes can autonomously learn representations of actions that are informative about their underlying goal. We show that the addition of an attention mechanism in the hidden space fosters the emergence of robust goal representations early on in the observation of an action sequence, making it a promising model for a robotic self-supervised general learner.
| Comments: | Presented at the poster session of the Workshop on World Models and Predictive Coding in Cognitive Robotics @ IROS2023 (this https URL) |
| Subjects: | Robotics (cs.RO); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.32688 [cs.RO] |
| (or arXiv:2610.32688v1 [cs.RO] for this version) | |
| https://doi.org/10.48550/arXiv.2610.32688 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Marco Gabriele Fedozzi [view email]
[v1]
Fri, 23 Oct 2026 14:19:34 UTC (1,598 KB)
来源：arXiv cs.AI · arxiv.org