ABM-Based Gaming Simulation For Policy Making

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Chapter 13 discussed managing complex systems and chapter 15 introduced the advantages of visual decision support. Discuss how you would combine the two concepts to create visualizations for an ABM-Based Gaming simulation for policy making. First, describe what specific policy you’re trying to create. Let’s stick with the SmartCity scenario. Describe a specific policy (that you haven’t used before), and how you plan to use ABM-Based Gaming to build a model for simulate the effects of the policy. Then, describe what type of visualization technique you’ll use to make the model more accessible. Use figure 15.9 and describe what data a new column for your policy would contain.

To complete this assignment, you must do the following:

A) Create a new thread. As indicated above, discuss how you would combine the two concepts to create visualizations for an ABM-Based Gaming simulation for policy making. First, describe what specific policy you’re trying to create. Let’s stick with the SmartCity scenario. Describe a specific policy (that you haven’t used before), and how you plan to use ABM-Based Gaming to build a model for simulate the effects of the policy. Then, describe what type of visualization technique you’ll use to make the model more accessible. Use figure 15.9 and describe what data a new column for your policy would contain.

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ITS 832 CHAPTER 15 VISUAL DECISION SUPPORT FOR POLICY MAKING: ADVANCING POLICY ANALYSIS

WITH VISUALIZATION

INFORMATION TECHNOLOGY IN A GLOBAL ECONOMY

DR. JORDON SHAW

 

 

INTRODUCTION

• Background

• Approach

• Case Studies • Optimization

• Social Simulation

• Urban Planning

• Conclusion

 

 

BACKGROUND

• Assessing policy options for societal problems is difficult

• Decision making methods • Data driven

• Model driven

• Visual decision supports helps in evaluating model output

• Information visualization and visual analytics • Makes complex results accessible to many

• Policy analysis • Part of process aimed at solving societal problems

 

 

DATA VISUALIZATION

 

 

POLICY CYCLE

 

 

APPROACH

• Characterization of stakeholders • Policy makers • Policy analysts • Modeling experts • Domain experts

• Public stakeholders

• Bridging knowledge gaps • With information visualization (IV) • Cohesive view of model representation

 

 

VISUAL SUPPORT FOR POLICY ANALYSIS

 

 

APPROACH, CONT’D.

• Synergy effects of applying IV to policy analysis

• Communication – facilitated

• Complexity – reduced

• Subjectivity – reduced

• Validation – improved

• Transparency and reproducibility of results – increased

 

 

CASE STUDIES

• Optimization • Optimization of regional energy plans considering impacts

• Environmental

• Economical

• Social

• Social Simulation • Simulation of the impact of different policy instruments on the adoption of photovoltaic (PV) panels by

homeowners

• Urban planning • Integration of heterogenous data sources in planning activities

 

 

SUMMARY OF CASE STUDIES

 

 

CONCLUSION

• Current model output is often difficult to understand • Not accessible for non-specialists

• Information visualization (IV) • Makes model output more accessible

• This paper applies IV to policy analysis

• Contributions • Defined collaborations

• Identified hurdles

• Defined interface methodology