English(EN) Path Channels and Plan Extension Kernels: a Mechanistic Description of Planning in a Sokoban RNN

Sokoban 游戏 AI 模型使用“路径通道”进行规划

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-28 04:00

研究人员部分逆向工程了用于 Sokoban 游戏的卷积循环神经网络 (RNN)。他们发现该网络将其未来移动或规划存储在其隐藏状态内的特定“路径通道”的激活中。这些通道受到编码学习到的转换模型的卷积核的影响，使 RNN 能够通过将激活从箱子传播到目标来构建规划，并使用负值在障碍物处修剪路径，从而有效地实现一种回溯形式。 AI

排序理由该集群包含一篇学术论文，详细介绍了训练神经网络中规划的新机制描述。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.AI TIER_1 English(EN) · Mohammad Taufeeque, Aaron David Tucker, Adam Gleave, Adri\`a Garriga-Alonso · 2026-05-28 04:00

路径通道与规划扩展核：Sokoban RNN 中规划的机制性描述

arXiv:2506.10138v3 Announce Type: replace-cross Abstract: We partially reverse-engineer a convolutional recurrent neural network (RNN) trained with model-free reinforcement learning to play the box-pushing game Sokoban. We find that the RNN stores future moves (plans) as activati…

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报道来源 [1]

路径通道与规划扩展核：Sokoban RNN 中规划的机制性描述

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