Recently, neural heuristics based on deep reinforcement learning have exhibited promise in solving multi-objective combinatorial optimization problems (MO-COPs).

Moreover, the model tends to generalize well to unseen tasks that did not appear in the training data.

KuaiRand Dataset and compare them against KuaiSim to further assess their performance and behavioral differences.

In the realm of multi-agent reinforcement learning (MARL), achieving high performance is crucial for a successful multi-agent system.

Due to the cost and risk of deploying autonomous vehicles (A Vs) in the real world, simulation is a crucial tool in the research and development of autonomous driving software.