##### AM-82 - Microsimulation and calibration of agent activities

- Describe a “bottom-up” simulation from an activity-perspective with changes in the locations and/or activities the individual person (and/or vehicle) in space and time, in the activity patterns and space-time trajectories created by these activity patterns, and in the consequent emergent phenomena, such as traffic jams and land-use patterns
- Describe how various parameters in an agent-based model can be modified to evaluate the range of behaviors possible with a model specification
- Describe how measurements on the output of a model can be used to describe model behavior

## AM-84 - Simulation Modeling

Advances in computational capacity have enabled dynamic simulation modeling to become increasingly widespread in scientific research. As opposed to conceptual or physical models, simulation models enable numerical experimentation with alternative parametric assumptions for a given model design. Numerous design choices are made in model development that involve continuous or discrete representations of time and space. Simulation modeling approaches include system dynamics, discrete event simulation, agent-based modeling, and multi-method modeling. The model development process involves a shift from qualitative design to quantitative analysis upon implementation of a model in a computer program or software platform. Upon implementation, model analysis is performed through rigorous experimentation to test how model structure produces simulated patterns of behavior over time and space. Validation of a model through correspondence of simulated results with observed behavior facilitates its use as an analytical tool for evaluating strategies and policies that would alter system behavior.