InfoTech in a Global Economy

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ITS832Chapter5.pdf

ITS 832 CHAPTER 5 FROM BUILDING A MODEL TO ADAPTIVE ROBUST DECISION MAKING USING SYSTEMS MODELING

INFORMATION TECHNOLOGY IN A GLOBAL ECONOMY

DR. JORDON SHAW

INTRODUCTION

• Systems modeling • Focus on decision making abilities

• Legacy System Dynamics (SD) modeling • Recent innovations • What the future holds • Examples

SYSTEMS MODELING

• Dynamic complexity • Behavior evolves over time

• Modeling methods • System Dynamics(CD) • Discrete Event Simulation(DES) • Multi-actor Systems Modeling(MAS) • Agent-based Modeling (ABM) • Complex Adaptive 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 DYNAMICS MODELING

• 1950s – Jay W. Forrester • Primary characteristics

• Feedback effects – dependent on their own past • Accumulation effects – building up intangibles

• Behavior of a 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 (Data Science) • Usability/accessibility advances

WHAT THE FUTURE HOLDS

• Better models • More data (“Big Data”) • Social media • Advanced capabilities for • Hybrid modeling • Simultaneous modeling

MODELING AND SIMULATION

EXAMPLES

• Assessing the Risk, and Monitoring, of New Infectious Diseases • Simple systems model with deep uncertainty

• Integrated Risk-Capability Analysis Under Deep Uncertainty • System-of-systems approach

• Policing Under Deep Uncertainty • Smart model-based decision support system

SUMMARY

• Modeling has long been used with complex systems • Recent evolutions have advanced modeling

• Increase computing power • Social media and Big data • Sophisticated analytics

• Multi-method and hybrid approaches are now feasible • Continued move into interdisciplinary study

• Advanced modeling for complex systems