2021/02/01 by Xing Su, Yan Kong, Su, Xing +3
Decision Sciences · #68T05 (Secondary) #68T42 (Primary) 68T01 #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #I.2.11 #I.2.6 #Scientific Computing and Data Management #Simulation Techniques and Applications
paper · pdf · doi:10.48550/arxiv.2102.01190
openalex publication_date 2021/02/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Computer-based modelling and simulation have become useful tools to facilitate humans to understand systems in different domains, such as physics, astrophysics, chemistry, biology, economics, engineering and social science. A complex system is featured with a large number of interacting components (agents, processes, etc.), whose aggregate activities are nonlinear and self-organized. Complex systems are hard to be simulated or modelled by using traditional computational approaches due to complex relationships among system components, distributed features of resources, and dynamics of environments. Meanwhile, smart systems such as multi-agent systems have demonstrated advantages and great potentials in modelling and simulating complex systems.