Write a summary about " Policy and Modeling in a Complex World" from Chapter 4 (Jansse, M., Wimmer, MA., & Deijoo 2015 Policy practice and digital science: integratin complex systems, social simulatio

ITS 832 Chapter 4 Policy Making and Modeling in a Complex World Information Technology in a Global Economy Professor Miguel Buleje Introduction • Policy Making and Modeling in a Complex World • Complexity • Managing Complex Systems • Modelling for Complex Systems Complexity • System composed of multiple interacting elements • Possible behavioral states can combine in ways that are hard to predict • Many complex systems in the physical world • Adaptive capacity of organisms allow for long -term survival in complex systems • Complex Adaptive Systems (CAS ) • Strong capacity to self -organize Double Pendulum Example Common Mistakes in Managing Complex Systems • Quantification • Policy is biased towards Q uantifiable V ariables. • Most often, monetary quantification . • Most often, solution selected would be favorable to the optimal economic outcome. • Commonly overlooks important non -quantifiable aspects • Compartmentalization • Second response by policymakers in trying to simplify complex system. • Attempts to simplify complex social systems • Large systems are split into smaller systems • High RISK to miss interactions between smaller systems • Spillover effect Complexity in Policy Making • Common approaches • Instrumental • Choosing between a set of possible policies • Evaluated based on past effectiveness • Requires • Large enough pool of available strategies • Effective assessment ofeffectiveness • Representational • Little more complication approach • Series of models • Each is assessed on its ability to predict observed behavior Instrumental Approach Representational Approach Agent - based Simulation Models • Agent -based simulation is presenting an optimal approach to address issue around complexity and policymaking. • Agent base models: • Represents individuals as separate computer models • Each model captures the behavior by each individual • Agents interact through a network • Distributed nature allows for realistic interactions , and makes this an attractive alternative. • SIMSOC • Simulated Society : use by universities and other groups to teach social sciences. • Large m odeling projects repository , per inventory on the SIMSOC, in our space of policy making. Summary • Complex systems are difficult to model • Interactions can be unpredictable • Common mistakes in modeling complex systems • Quantification • Compartmentalization • Two common approaches to complex system modeling • Instrumental • Representational • Agent -based modeling