Agent-based modeling and simulations (ABMS) is a new approach to modeling systems consisting of autonomous, interacting agents. Agent-based modeling offers ways to more easily model individual behaviors and how that same behavior affects others. There is great interest in developing agent-based models to solve modeling and simulation problems more quickly and efficiently. Different situations and systems are characterized by the presence of autonomous entities whose local ones determine the evolution of the entire system. Agency models are particularly suitable for supporting the definition of models of such systems, but also for supporting the design and implementation of simulators. Agent-based models and multi-agent systems (MAS) have been adopted to simulate very different types of complex systems, from simulating socio-economic systems to developing scenarios for logistics optimization, from biological systems to urban planning. The application of this II modeling method is used in the stock market, supply chains and consumer markets, all the way to predicting the spread of epidemics, traffic regulation and more. Such progress reveals the potential of ABMS and encourages the increasing use of this method. Some argue that ABMS is a third way of engaging with science and could increase traditional deductive and inductive reasoning as methods of discovery.