complex networks; combinatorial optimization; deep reinforcment learning; reward shaping MSC: 90C27; 05C851. Introduction Complex networks hold substantial significance given their extensive reach and impact on diverse aspects of our lives. At the heart of complex networks lie the key players, also ...
The proposed approach is potentially useful for driving in dynamic constrained scenarios when dangerous collision events might occur frequently with classic DRLs. The experimental results show that the proposed autonomous driving behavior learning method exhibits online learning capability and environmental ...
The proposed approach is potentially useful for driving in dynamic constrained scenarios when dangerous collision events might occur frequently with classic DRLs. The experimental results show that the proposed autonomous driving behavior learning method exhibits online learning capability and environmental ...