Management of Complex Systems: Toward Agent-Based Gaming for Policy – this should include below 4 modules:
- CHAPTER SUMMARY: Summarize chapter presented during the week. Identify the main point (as in “What’s your point?”), thesis, or conclusion of the key ideas presented in the chapter.
- SUPPORT: Do research outside of the book and demonstrate that you have in a very obvious way. This refers to research beyond the material presented in the textbook. Show something you have discovered from your own research. Be sure this is obvious and adds value beyond what is contained in the chapter itself.
- EVALUATION: Apply the concepts from the appropriate chapter. Hint: Be sure to use specific terms and models directly from the textbook in analyzing the material presented and include the page in the citation.
- SOURCES: Include citations with your sources. Use APA style citations and references.
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