Swarm intelligence algorithms are a subset of the artificial intelligence (AI) field, which is
increasing popularity in resolving different optimization problems and has been widely …

The rapid development of urban cities coupled with the rise in population has led to an
exponentially growing number of vehicles on the roads for the latter to commute. This is …

The Metaverse depicts a parallel digitalized world where virtuality and reality are fused. It
has economic and social systems like those in the real world and provides intelligent …

Exploiting reinforcement learning (RL) for traffic congestion reduction is a frontier topic in
intelligent transportation research. The difficulty in this problem stems from the inability of the …

Intelligent transport systems, efficient electric grids, and sensor networks for data collection
and analysis are some examples of the multiagent systems (MAS) that cooperate to achieve …

Finding the optimal signal timing strategy is a difficult task for the problem of large-scale
traffic signal control (TSC). Multiagent reinforcement learning (MARL) is a promising method …

As the number of vehicles grows rapidly each year, more and more traffic congestion occurs,
becoming a big issue for civil engineers in almost all metropolitan cities. In this paper, we …

Traffic signal control can mitigate traffic congestion and reduce travel time. A model-free
reinforcement learning (RL) approach is a powerful framework for learning a responsive …

The spread of intelligent transportation systems in urban cities has caused heavy
computational loads, requiring a novel architecture for managing large-scale traffic. In this …

With the development of economic globalization and sustainable manufacturing, sustainable
scheduling of distributed manufacturing has attracted increasing concern. However …