most citedMODRL/D-AM: Multiobjective Deep Reinforcement Learning Algorithm Using Decomposition and Attention Model for Multiobjective Optimization

2 citations · 2 across the 1 of their papers we have counts for

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1 paper

cs.NE2020★ 2 cited

MODRL/D-AM: Multiobjective Deep Reinforcement Learning Algorithm Using Decomposition and Attention Model for Multiobjective Optimization

Hong Wu, Jiahai Wang, Zizhen Zhang

Recently, a deep reinforcement learning method is proposed to solve multiobjective optimization problem. In this method, the multiobjective optimization problem is decomposed to a…