Simulating the Tragedy of the Commons
Using Agent-Based Modeling
Josh Lee
Computer Systems Lab 08/09
Abstract
Tragedy of the Commons
-autonomous individuals
-communal resources
Experimental Economics
-conventional economic wisdom
Agent-Based Modeling
-agent types
-NetLogo
The Tragedy of
the Commons
Example: Waste
-individuals contributing to group problem
-finite resources
Sahel
-three-tier model
-more complex, but more realistic/practical
Background
“Understanding the Tragedy of the Sahel,” Corey
L. Lofdahl
-original Tragedy of the Commons ABMS
“The Tragedy of the Commons,” Garrett Hardin
-max goods v. max population
-stabilization
”Artificial Agents Learning Human Fairness”
- 'Continuous Action Learning Automata' and the
'Homo Equalis utility function'
-quantative evaluation
System Dynamics v.
Agent-Based Modeling
Sahel, overshoot-and-collapse
Individual agent behavior
-agent cooperation (or lack thereof);
experimental economics
-emergent behavior, dominant behavior
types
Fig. 1: Model, Upon Opening
Model Overview
Adjustable Parameters
“grass-growth-rate”
“grass-energy”
“cattle-energy”
Likelihood of finding resources
Example:
-greater grass-growth-rate
>greater cattle population
>lower grass count
>greater competition
-long-term, greater instability
Fig. 2:
Population
Fluctuations
(Instability)
Additional Features
Drought
Length, frequency
Demonstrates instability
Behavior Alterations
Degrees of altruism (behavior types)
Expand awareness
-available grass, people
Future Development
Homo Egualis Utility function
Numerically evaluate success
Emergent Behavior
Dominant behavior type
Population stability
Problems
Difficulty managing population trends
Cattle populations unstable
-sustaining losses appropriately
-recovering over an appropriate time span
Difficulty implementing awareness/altruism
Fig 4: Unique Emergent Behavior