使.

Xiaoyu Fu1, Shenshen Gu1, Chee-Meng Chew2

  • 1School of Mechatronic Engineering and Automation, Shanghai University, 99 Shangda Road, Shanghai, 200444, China.

概括

本研究介绍了一种新的深度强化学习算法,即交叉融合注意网络 (CFAN),以有效地解决复杂的多目标旅行销售员问题. 在各种问题实例中,CFAN表现出卓越的性能和概括性.

相关概念视频

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Reinforcement Schedules01:24

Reinforcement Schedules

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Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

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Reducing Line Loss01:18

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Associative Learning01:27

Associative Learning

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