DM-DQN: Dueling Munchausen deep Q network for robot path planning

DM-DQN: Dueling Munchausen deep Q network for robot path planning

Abstract In order to achieve collision-free path planning in complex environment, Munchausen deep Q-learning network (M-DQN) is applied to mobile robot to learn the best decision. On the basis of Soft-DQN, M-DQN adds the scaled log-policy to the immediate reward. The method allows agent to do more e...

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Bibliographic Details
Main Authors: Yuwan Gu, Zhitao Zhu, Jidong Lv, Lin Shi, Zhenjie Hou, Shoukun Xu
Format: Article
Language:English
Published: Springer 2022-12-01
Series:Complex & Intelligent Systems
Subjects:
Deep reinforcement learning
DM-DQN
Path planning
Dueling network
Online Access:https://doi.org/10.1007/s40747-022-00948-7

Internet

https://doi.org/10.1007/s40747-022-00948-7

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