Beijing University of Technology Researcher Updates Understanding of Robotics (An Improved Dyna-Q Algorithm Inspired by the Forward Prediction Mechanism in the Rat Brain for Mobile Robot Path Planning)

北京工业大学研究员更新了对机器人的理解(基于大鼠脑前向预测机制的改进Dyna-Q算法在移动机器人路径规划中的应用)

Robotics & Machine Learning Daily News2024，Issue(Jun.12) ：8-9.

来源：

NETL
NSTL

Beijing University of Technology Researcher Updates Understanding of Robotics (An Improved Dyna-Q Algorithm Inspired by the Forward Prediction Mechanism in the Rat Brain for Mobile Robot Path Planning)

北京工业大学研究员更新了对机器人的理解(基于大鼠脑前向预测机制的改进Dyna-Q算法在移动机器人路径规划中的应用)

扫码查看

摘要

由一名新闻记者-机器人与机器学习的工作人员新闻编辑每日新闻-机器人的新数据在一个新的报告中呈现。根据NewsRx编辑的《中华人民共和国北京消息》报道，该研究指出："传统的基于模型的强化学习(MBRL)算法在机器人空间认知和导航任务中计算量大，收敛性差，性能较差，不能充分解释动物快速适应环境变化和学习各种复杂任务的能力"。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News-Fresh data on robotics are presented in a new rep ort. According to news originating from Beijing, People’s Republic of China, by NewsRx editors, the research stated, “The traditional Model-Based Reinforcement Learning (MBRL) algorithm has high computational cost, poor convergence, and poo r performance in robot spatial cognition and navigation tasks, and it cannot ful ly explain the ability of animals to quickly adapt to environmental changes and learn a variety of complex tasks.”

Key words

Beijing University of Technology/Beijin g/People's Republic of China/Asia/Algorithms/Emerging Technologies/Machine Learning/Reinforcement Learning/Robot/Robotics

引用本文复制引用

出版年

2024

Robotics & Machine Learning Daily News

ISSN：

段落导航