InfoTech in a Global Economy
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