A Generic Agent-Based Model of Historical Social Behaviors Change

Abstract

The primary theme of this chapter is trying to describe, discuss and understand how human societies change over time using agent-based modeling. Agents become a major paradigm of social simulation allow us to model the complex social phenomena under the bottom-up approach. Certainly one of the key points of the bottom-up approach is the emergence of macro level phenomena from micro level actions and interactions. The main objective of this work is to build a Virtual Social Laboratory, from Rafael Pla Lopez Social evolution model, in order to explore the social evolution of a set of artificial societies/agents that evolve within a grid of cells which are characterized by a level of natural resources (artificial environment). This laboratory can help to explore and understand the East–West duality, the North–South Divide, the Human migration process, the globalization-polarization and some possible human social evolution.

Appendix

The model is implemented in java source code

• 1. Class SocialVisualizer that implements a graphical interface as a grid to visualize the dynamic model

• 2. Class SocialModel that implements the two-layer structure of Model (Resources and agents). The main tasks (methods) are:

  Initialization:

  • Initialize “constants” (parameters of the model) from configuration file

  • Create resources

  • Initializes resources

  • Create agents (list of Societies Live)

  • Initializes agents (Initializes memory, probability, Repressive Capacity and Suffered Social Repression)

Main loop

public void run() { for ( T=0 ; T <= Tmax ; T += deltaT ) { for ( nAgent = 0; nAgent < listAgent.length; nAgent ++) { listAgent[nAgent].updateAgent(listAgent); } if ( getNumberAgentLive() == 0 ){ fLog.println("End: are not living systems."); break; } migration(); updateResources(); sleep(delay); } }

• 3. Class Agent that implements dynamics and evolution of internal agent processes. The main methods are:

Initialization:

public void init() { initAccumulatedMemory(); initForce(); initFerocity(); initSatisfactionCapacity(); initRepressiveCapacity(); }

Update Agent:

public void updateAgent( Agent [] listAgents ) { if( this.isLive() ){ updateProbability(); updateSocialSufferedRepression(listAgents); updateRepressiveCapacity(); updateSatisfactionFunction(); updateAccumulatedMemory(); updateResourceAgent(); if( ! this.isDeath() ){ checkProgress (); } }else{ checkRecuperation(); } }