This document discusses using agent-based modeling and simulation through serious games to study leadership and management in complex systems. It proposes developing games that allow players to take on leadership roles and test different styles as they interact with an autonomous artificial intelligence population. This could help evaluate which styles work best in different scenarios and determine the optimal choice. Both single-player and multiplayer settings are suggested to realistically simulate the dynamic relationships and consequences of decisions in complex environments. The goal is to provide an interactive way to experiment with and measure behaviors as players respond to complex situations and other actors.

1. Chapter 9 – Proofreading Exercise
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A critical process in technology management is measuring
performance and
managing information. As noted by numerous authors and
researchers, focusing on the
wrong areas can lead to actions that don’t help the organization
relize there strategic goals. This is one of the ways that a
balanced
scorecard approach can prove beneficial, since it helps the firm
identify the

3. proper measures by allaying them with the firms vision
and strategy. Specifically, performance measures should align
with
the principal factors that determinate the success for that
particular firm.
It’s impotent to note that a firm could be meeting these
specific requirements and still not be in a position to acheive
it’s
long-term goals. This problem can be addressed at least in part
by
ensuring that the performance measures are used at the
appropriate level
within the organization. If the organization ensures that there
are goals for
each level of the organization, and appropriate measures that
correspond too these goals, than it stands a much better chance
of aligning its performance measures with it’s strategic intent.
This means
that their should be goals and corresponding measures that are
used at
the corprate level, the factory level (in the case of a firm in the

4. manufacturing industry) and the production line level.
As we can see, identifying the proper performance measures
can be
difficult. That having ben said, so long as the firm uses the
proper criterion to select data and uses that data correctly it will
have a much better chance of finding and sustaining an
competitive
advantage.
ITS 832
Chapter 15
Visual Decision Support for Policy Making: Advancing
Policy Analysis with Visualization
Information Technology in a Global Economy
Professor Michael Solomon
Introduction
• Background
• Approach

5. • 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

6. 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

7. • 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

8. • This paper applies IV to policy analysis
• Contributions
• Defined collaborations
• Identified hurdles
• Defined interface methodology
ITS 832
Chapter 13
Management of Complex Systems:
Toward Agent-Based Gaming for Policy
Information Technology in a Global Economy
Professor Michael Solomon
Introduction
• Simulating/Managing Social Complex Phenomena
• Leadership and Management in Complex Systems
• Serious Gaming
• Agent-Based Games for Testing Leadership and
Management
• Single and Multiplayer Settings
• Summary and conclusions

9. Simulating and Managing Social
Complex Phenomena
• Study of how people interact
• Scale prohibits experimentation with real populations
• Agent-Base modeling (ABM)
• Networked agents
• Each agent is an individual
• Interaction may modify agent behavior
• Managing complex phenomena introduces complexity
• Techniques to manage turbulent situations vary
• Technique success depends on responding to agent behavior
• Which may change based on interactions
Leadership and Management in
Complex Systems
• Traditional leadership research
• Generally focuses on single period in time
• Doesn’t address dynamic relationships
• Timing of leadership principle application matters
• Primary leadership functions
• Instructional and regulatory

10. • Developmental
• Simulations offer promise to help model leadership in
complex systems
Serious Gaming
• Applying gaming techniques to real life situations
• Flight simulators
• Effective for evaluating complex environments
• Player must interact with multiple actors and situations
• Currently used for side range of training applications
• Leadership use
• Deterministic – limited scope
• ABMs in serious gaming can help understand more complex
interactions
Agent-Based Games for Testing
Leadership and Management
• ABM games with autonomous AI population
• Test leadership style effectiveness
• Explore which styles work best in different situations
• Determine the best choice for a given scenario
• Current state of the art is more conceptual

11. • Advances needed in interfaces
• Need to allow users to interact with simulation
• Keep players engaged
Behavior Impacted by Multiple Factors
Single and Multiplayer Games
• AI may react poorly to management input
• Simulating unexpected consequences of decisions
• Overactive AI may degrade realism
• Players can dynamically see how decisions affect others
• Early simulations allow for only single players
• Multiple real players adds more realistic interaction
• Players replace some AI
• Players interact with each other and AI
Summary and Conclusions
• ABM-based gaming can measure behaviors of players
• Supports experimentation in controlled environment
• Study leaderships and management in complex systems

12. • Focus
• Interaction with leadership
• Interaction with players as a result of leadership action