Week 6

ITS 832

Chapter 5 From Building a Model to Adaptive Robust Decision MakingUsing Systems Modeling

Information Technology in a Global Economy

Introduction

• Systems modeling • Focus on decision makingabilities

• Legacy System Dynamics (SD)modeling

• Recent innovations

• What the futureholds

• Examples

Systems modeling

• Dynamic complexity • Behavior evolves overtime

• Modeling methods • System Dynamics (CD) • Discrete Event Simulation(DES) • Multi-actorSystems Modeling (MAS) • Agent-based Modeling (ABM) • ComplexAdaptive Systems Modeling (CAS)

• Enhanced computing supports model based decision making • Modeling and simulation has become interdisciplinary

• Operation research, policy analysis, data analytics, machine learning, computer science

Legacy System DynamicsModeling

• 1950s – Jay W.Forrester

• Primary characteristics • Feedback effects – dependent on their own past

• Accumulation effects – building up intangibles

• Behavior ofa system is explained • Casual theory – model generates dynamic behavior

• Works well when • Complex system responds to feedback and accumulation

Recent Innovations

• Detailed list of individual innovations

• Deep uncertainty • Analysts do not know or cannot agree on

• Model

• Probability distributions of key features

• Value of alternative outcomes

• Two primary evolutions • Smarter methods (DataScience)

• Usability/accessibility advances

What theFuture Holds

• Better models

• More data (“BigData”)

• Social media

• Advanced capabilities for • Hybrid modeling

• Simultaneous modeling

Modeling andSimulation

Examples

Assessing the Risk, and Monitoring, of New Infectious

 Diseases

Simple systems model with deep uncertainty

Integrated Risk-CapabilityAnalysis Under Deep

 Uncertainty

System-of-systems approach

Policing Under DeepUncertainty

Smart model-based decision support system

Summary

• Modeling has long been used with complex systems

• Recent evolutions have advancedmodeling • Increase computing power

• Social media and Big data

• Sophisticated analytics

• Multi-method and hybrid approaches are now feasible

• Continued move intointerdisciplinary study • Advanced modeling for complex systems