Multi-Agent Modeling of Societal Development and

Cultural Evolution

Yidan Chen, 2006Computer Systems Research Lab

Abstract The "bottom-up" approach Implementing the background world and individualized agents

with specific attributes The Multi-Agent Simulator of Neighborhoods (MASON) library Simple rules to regulate agent behavior Agent-based simulations with correlating results to historically

recorded migration developments Complex behavior results through economic aspects of wealth

distribution and trade, and social aspects of reproduction, death, health, and cultural exchange.

Scope

Initially limited to basic rules of survival (food/migration)

Incorporate the ideas of life and death into Sugarscape

Variable values for basic parameters Implement more complex rules with time

(intergroup relations/ disease)

Background1

Concept of life as Information Research in areas of artificial life Conway's Game of Life First known case of artificial life Finite initial configurations generate an

infinite population Complex implications from simple rules

Background 2

Implications of Conway's Life Leads to bottom-up models of real world

situations Graig Reynolds's “boids” Computational model of decentralized

activity Based on individual rules No centralized control

Background 3

Robert Axtell & Joshua M. Epstein's Sugarscape

Simple rules cause aggregate effects Based on interactions between Agents Proto-history, cultural evolution,

population development, etc.

World

Value of each cell corresponds to map

Sugar grows back with each step, rate dependent on growth rule

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Agents

Metabolism – Int between 1 & maxSugar Vision – Int between 1 & 8 Collects all sugar in cell with each step Moves to closest cell with highest sugar

value

Methodology

Build on the algorithm of another program (Schelling and Heatbugs in MASON)

First prototype to duplicate growth rule (RuleG)

Duplicate simple agent functions (takeSugar, reaper, step)

Some other stuff that didn't happen

2D Representation

Agents represented by red circles

Sugar show in yellow

More yellow represents greater density

Testing

Agents start in square at top corner

Movement in waves towards other pole of sugar

Consistent

3D Representation

3D based off of HeatBug3DWithUI

Uses Java3D – remote does not work (applet)

Results 1

Initially migration pattern some error

Tendency to move back and forth in the horizontal direction, or a tendency to bypass closer cells with equal amounts of sugar.

Results 2

Implementation of a distance check in step() method

Agents start with randomly assigned positions

Pick the optimal position and continue to advance

Results 3

Sugar growthRate is a limited number {RuleG}

Agents all migrate to the poles

Agents form congregation at the center of the poles

Conclusion 1

The basic statistics recorded and displayed through the use of screen shots and graphs

The patterns of migration in the agents show interesting insight into progression of a population when a limited resource is in question.

Conclusion 2

When each member of a society acts for its own benefits, an aggregate pattern of either gathering at lattices or wave movement is distinct

Through decentralized rules, the society creates seemingly centralized activity

Sources

Axtell,R. & Epstein, J.M. Growing Artificial Societies, Brookings Institution Press, Washington, D.C, 1997.

“Introducing Sugarscape”, The Brookings Institute, 20 Jan 2006. <http://www.brook.edu/es/dynamics/sugarscape/default.htm>