The%20RePast%20Framework%20and%20Social%20Simulations

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The RePast Framework and Social Simulations

• Presented by Tim Furlong

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Overview

• RePast
• Social Simulations
• Simulations implemented with RePast
• Santa Fe Artificial Stock Market
• Endogenizing Geopolitical Boundaries

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RePast

• REcursive Porous Agent Simulation Toolkit
• Java class library
• University of Chicago
• Social Science Research Computing

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RePast Framework

• Base classes to be extended
• Engine class
• Agent class
• Environment class
• GUI displays, charts, graphs
• Utility classes
• Spatial representations
• Statistical RNGs

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• Generic approach
• Discrete event simulator
• Easy implementation
• SugarScape(partial) 650 LOC
• Game of Life 750 LOC

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RePast Advantages

• Facilitates implementation
• Convenient representation of heterogeneous agents
• Support for geometric world models
• Garbage collection
• Powerful visualization techniques
• Lars-Erik Cederman, Endogenizing Geopolitical
  Boundaries with Agent-based Modeling, prepared
  for Sackler Colloquium on Adaptive Agents,
  Intelligence, and Emergent Human Organization
  Capturing Complexity through Agent-based
  Modelling, Oct. 2001.

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RePast Applications

• School voucher programs
• Consumer choice
• Decision making in closed regimes
• Modeling the size of wars
• Voting dynamics
• Self-organizing computer networks
• Multi-cellular tumors
• Repast Homepage Projects and Publications
  http//repast.sourceforge.net/projects.html

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Social Simulations

• Goal is to simulate observed behaviors with
  hypothesized model
• Several flavors of simulation
• Statistical global variables
• Agent-based allows heterogeneous agents with
  varied and dynamic behavior

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The Santa Fe Artificial Stock Market Re-Examined
Suggested Corrections

• Norman Ehrentreich

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SFI-ASM Introduction

• Simplistic stock market simulation
• Isolates learning speed of traders as critical
  parameter
• Based on original SFI-ASM
• Fixes faulty mutation operator
• Results not quite as compelling
• Interesting RePast model

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SFI-ASM Original Model

• N traders
• 1 unit risky stock, 20 000 units cash
• Each trader seeks to buy or sell stock based on
  expectations of profit
• Profit
• Fixed return of rf on cash assets
• Stock pays stochastic dividend

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SFI-ASM Stock

• Only one stock in market
• Stock has price pt and dividend dt
• Dividend of stock at time t 1
• Mean-reverting factor of (1 ?), but generally
  stochastic

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SFI-ASM Traders

• Risk aversion factor of ?i
• Wealth at time t of Wi,t stock cash
• Optimal amount of stock based on expectations of
  profit

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SFI-ASM Expectation rules

• Market has descriptor Dt
• Bitstring of market conditions
• Each trader has own set of 100 rules
• Rule comprised of
• Condition
• Forecast
• Forecast accuracy
• Fitness value

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• Condition is pattern matching rule
• String of 0,1,
• Bits are technical or fundamental
• Forecast for rule j (aj,bj)

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• Forecast Accuracy
• Fitness Value

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SFI-ASM Rule Evolution

• Genetic algorithm invoked after every K rounds of
  trading to evolve rules
• Mutation (p0.7)
• Crossover

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SFI-ASM Correction

• Original had faulty mutation operator
• Biased results to higher number of non- bits
• Correct solution for rules is to converge to
  all- bits
• Dividend and price too random to classify
• With new operator, rules always converge

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SFI-ASM Results

• Rules converge to all- bits
• Reach homogeneous rational expectation
  equilibrium eventually
• With values for K lt 100, complex trading emerges
• Harder to persuade the model to do this with the
  new mutation operator

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• Faster learners exploit slower learners
• Short-term trends
• In new model, only valid in beginning

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Endogenizing Geopolitical Boundaries with
Agent-based Modeling

• Lars-Erik Cederman

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EGB Introduction

• Agent-based modeling has potential to avoid
  reification of actors
• Reification treating an abstract concept as
  concrete
• Long-term simulations require sociational
  endogenization of actors
• Actors must be internally dynamic

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EGB Background

• Essentialist perspective
• Ignore change of actors
• Fixed entities with attributes
• Sociational perspective
• Dynamic actors and relationships
• Context-sensitive

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EGB Endogenization

• Presents series of models to illustrate
  progression from reified actors to endogenous
  ones
• Modeling emergence of state borders
• Emergent Polarization (EP)
• Democratic Peace (DP)
• Nationalist Systems Change (NSC)

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EGB Emergent Polarization

• Models conquest and expansion of states
• Villages or counties on a finite 2d grid
• States emerge as villages conquer neighbors
• State has capital based on original village
• Resources gathered from the territories depends
  on distance to capital

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EGB EP turn structure

• Five phases per turn
• Resource allocation
• Decisions
• Interaction
• Resource updating
• Structural change

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• Resource allocation
• Allocate troops to borders based on strength of
  neighbors
• Decisions
• Reciprocate aggressive action
• Attempt unprovoked attacks

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• Interaction
• Resolve conflicts based on balance of power
• Resource updating
• States gain resources from provinces
• Structural change
• Structure of defeated state altered by outcome of
  conflicts

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• Notes
• States can spread too thin, inviting attack from
  other neighbors and opening multiple fronts to
  conflict
• Can extend the model to allow alliances between
  states

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EGB Democratic Peace

• Adds categorical relationships to previous model
• Observed that democracies do not fight each other
• Add democracy label to some states
• Democracies do not fight each other, and form a
  defensive coalition

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• Notes
• Difference in balance of power produces
  significant results
• Example of adding categorical social processes
• Threat evaluation is still relational

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EGB Nationalist Systems Change

• Introduce concept of actors separate from states
  nations
• Nations and states sometimes coincide, but not
  always
• Each village has cultural identity string of
  trait values
• Nation is a pattern string of traits with
  wildcards

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• Nations founded and joined by agents
• Capitals more likely to found nations due to
  resources
• National identities have major impact on
  inter-state relations
• irredentist invasions to conquer conationals
  not under home rule

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EGB Conclusions

• Agent-based simulations are better at modeling
  complex phenomenae than conventional approaches
• Treating actors as themselves emergent and
  internally dynamic is necessary to good
  simulation over long time scales

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Questions?