论文标题
基于海马地方领域的新型模型，快速学习目标导向导航的空间表示
Rapid Learning of Spatial Representations for Goal-Directed Navigation Based on a Novel Model of Hippocampal Place Fields
论文作者
论文摘要
在啮齿动物的海马复合物中发现位置细胞和其他空间调节神经元的发现对于阐明空间认知的神经基础至关重要。最近，已经观察到在完整的行为期间观察到编码以前经历过的轨迹的神经序列的重播，这可能对快速记忆巩固和行为计划产生影响。根据这些发现和以前的发现，已经提出了一些用于机器人导航和强化学习的有前途的模型。但是，大多数模型都使用精心设计的神经网络，并在简单的环境中进行了测试。在本文中，我们开发了一个自组织模型，结合了位置细胞并重播，并证明了其在具有障碍的非平凡环境中快速单次学习的实用性。
The discovery of place cells and other spatially modulated neurons in the hippocampal complex of rodents has been crucial to elucidating the neural basis of spatial cognition. More recently, the replay of neural sequences encoding previously experienced trajectories has been observed during consummatory behavior potentially with implications for quick memory consolidation and behavioral planning. Several promising models for robotic navigation and reinforcement learning have been proposed based on these and previous findings. Most of these models, however, use carefully engineered neural networks and are tested in simple environments. In this paper, we develop a self-organized model incorporating place cells and replay, and demonstrate its utility for rapid one-shot learning in non-trivial environments with obstacles.
