Modeling and Simulation
The Modeling and Simulation (M&S) discipline and its enabling technologies support hundreds of important application areas requiring decision-support (such as prediction, evaluation, testing, planning, acquisition, and proof-of-concept), understanding, and education, as well as training to develop and/or enhance motor skills to gain proficiency in the use of equipment, decision-making by getting experience in controlled environments.
At the dawn of 21st century, as also acknowledged in 2007 by the US Senate House Resolution 487, M&S is a critical area for the well-being of advanced countries. Decision makers increasingly encounter challenging policy problems that involve systems composed of large number of diverse interacting elements. To address these problems, major advances in computational simulation technologies have catalyzed research in science of complexity, enabling engineers and scientists to create large numbers of virtual system agents and set them to interact with each other in simulated worlds. Among such problem domains that require timely or even urgent policy formation and informed decision-making include long-term climate change, innovation dynamics, healthcare systems, disaster management, environmental protection, economic forecasting, energy security (including generation, distribution, storage and utilization of energy), the dynamics of conflicts, the design of financial regulatory systems, and the epidemiology of diseases. By developing simulations and varying their parameters, researchers can explore the consequences of wide spectrum of emergent and non-linear collective behaviors, and verify and validate theoretical models by comparing them with their real-world counterparts.
