Timing Agent Interactions for Efficient Agent-Based Simulation of Socio-Technical Systems

摘要: In recent decades, agent-based modeling and simulation (ABMS) has been increasingly used as a valuable approach for design analysis of dynamic emergent phenomena large-scale, complex multi-agent systems, including socio-technical systems. The behavior such systems includes both the individual heterogeneous agents within system arising from interactions between their work environment; must be accurately modeled efficiently executed in simulations. An important issue ABMS is ensuring that are updated together at any time where they interact or exchange data, even when agents’ internal models use fundamentally different methods advancing widely varying update rates. This requires accurate predictions interaction times environment. Predicting interactions, however, not trivial problem. Thus, timing mechanisms advance select proper agent to crucial correct results. chapter describes prediction mechanism among which also increases computational efficiency experiment comparing highlighted gains achieved with new emphasized importance identifying times. intelligent framework predicting using neural network method assessing accuracy based on signal detection theory described. application air transportation serves test case results presented. insights discussed.