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ITS 832
Chapter 13
Management of Complex Systems:
Toward Agent-Based Gaming for Policy
Information Technology in a Global Economy
Professor Miguel Buleje
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
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
• 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
• Agent Based Modeling (ABM)s in serious gaming can help
understand more complex interactions
Agent-Based Games for Testing
Leadership and Management
• Agent Based Modeling (ABM) games with
autonomous Artificial 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
• Advances needed in interfaces
• Need to allow users to interact with simulation
• Opportunity to 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
• Agent Based Modeling (ABM) - based gaming can
measure behaviors of players
• Supports experimentation in controlled environment
• Study leaderships and management in complex systems
• Focus
• Interaction with leadership
• Interaction with players as a result of leadership action

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ITS 832Chapter 13Management of Complex Systems Towar.docx

  • 1. ITS 832 Chapter 13 Management of Complex Systems: Toward Agent-Based Gaming for Policy Information Technology in a Global Economy Professor Miguel Buleje 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 Simulating and Managing Social Complex Phenomena
  • 2. • 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 • Developmental • Simulations offer promise to help model leadership in complex systems
  • 3. 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 • Agent Based Modeling (ABM)s in serious gaming can help understand more complex interactions Agent-Based Games for Testing Leadership and Management • Agent Based Modeling (ABM) games with autonomous Artificial 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 • Advances needed in interfaces • Need to allow users to interact with simulation • Opportunity to keep players engaged
  • 4. 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 • Agent Based Modeling (ABM) - based gaming can measure behaviors of players • Supports experimentation in controlled environment • Study leaderships and management in complex systems • Focus • Interaction with leadership
  • 5. • Interaction with players as a result of leadership action