Week 11- info tech

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

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

• 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 • 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

• Focus • Interaction with leadership

• Interaction with players as a result of leadership action