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Money,  Sex  and  Evolu0on   Agent-­‐based  modeling   with  Ruby   Chang  Sau  Sheong   PayPal   March  2014  

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About  me  

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Common  Starling  (Sturnus  vulgaris)  

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•  Boids  by  Craig  Reynolds   •  Models  animal  mo0ons   through  simple  rules,  resul0ng   in  flocking  behavior   •  Emergent  behavior  –  complex   behavior  arising  from  simple   rules   •  Eventual  basis  for  some  of  the  more  impressive   cinematographic  anima0on  –  Lord  of  the  Rings,   Batman  Returns,  Lion  King  etc  

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3  simple  rules   •  Separa0on   – Move  to  avoid  crowding  in  the   flock   •  Alignment   – Move  in  the  same  direc0on  as   the  flock   •  Cohesion   – Move  towards  the  center  of  the   flock  

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Agent-­‐based  modeling     •  Also  known  as  mul0-­‐agent  simula0on   •  Autonomous  agents  interac0ng  with  each   other  and  the  environment   •  Used  in  analysing  supply  chain  op0miza0on,   traffic  paRerns,  economic  models,  spread  of   epidemics   •  Influenced  by  John  Conway’s  Game  of  Life   •  Heavily  influenced  by  Epstein  and  Axtell’s   Sugarscape  simula0ons  

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Utopia   •  Ar0ficial  world  called  Utopia   •  Populated  by  roids  (implementa0on  of  boids   in  Ruby)   •  Free  to  wander  through  an  infinite  landscape   •  Simula0ons  are  created  with  Ruby  and  the   Gosu  library  

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Base  simula0on  

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Why  does  income   inequality  exist?  

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Change  behavior  in  base  simula0on   •  Roids  now  have  an  energy  level  (randomly   assigned)   •  At  every  0ck,  roids  lose  1  energy   •  If  energy  level  reaches  0,  it  will  die   •  To  prevent  this,  it  will  ac0vely  seek  out  food   and  consume  it   •  Consuming  food  replenishes  energy  level   •  (But  roids  are  s0ll  immortal)  

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Data  collec0on   •  At  every  0ck  record  the  energy  level  of  each   roid   •  Do  this  un0l  the  end  of  the  world  (simula0on   completes)  

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First  simula0on  

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Energy  level  analysis  

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On  the  day  of  reckoning   Most  roids  are  dead   A  few  roids  have  a   lot  of  energy  

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Gini  coefficient  and  Lorenz  curve   •  The  Gini  coefficient  is  a   measure  of  the  inequality  of   a  distribu0on,  0  is  perfect   equality  and  1  is  perfect   inequality   •  Defined  mathema0cally   based  on  the  Lorenz  curve   Area  is  the  amount   of  inequality  

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Lorenz  curve  on  inequality   Not  much   inequality   A  lot  of   inequality!  

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Observa0on   •  Over  a  period  of  0me,  a  small  percentage  of   the  popula0on  gets  a  large  propor0on  of  the   energy   •  What  is  the  cause  of  this?  

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Why  the  inequality?   •  Hard  work  and  inherent  talent/ability?   – All  roids  are  the  SAME   •  Some  roids  luckier  than  others  i.e.   random  distribu0on?   – If  it’s  random  then  it  should  follow  a  normal   distribu0on  

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The  rich  get  richer,  the  poor  get   poorer   •  Back  to  where  we  started  –  emergent   behavior   •  Small  changes  ripple  down  to  large  effects   over  a  period  of  0me   •  Simple  local  rules  brings  complex  global   changes  

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Spicing  things  up  with  sex   •  Roids  have  gender  now  –  male  and  female   •  Males  are  blue,  females  are  red,  underaged  are     •  If  female  is  within  childbearing  age  (25  to  50   0cks)  and  if  it  has  enough  energy,  it  will  look  for  a   nearby  male     •  If  male  is  also  within  childbearing  age  and  have   enough  energy,  they  will  procreate  and  produce   a  baby  roid   •  Both  male  and  female  loses  energy  each  0me   they  procreate  

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Grim  reaper  arrives   •  With  birth  we  introduce  death   •  Each  roid  has  a  randomly  assigned  lifespan   •  Each  0ck  increases  the  age  of  the  roid   •  Roid  dies  when  it  reaches  its  lifespan  

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Data  collec0on   •  We  want  to  inves0gate  how  the  popula0on   changes  once  we  introduce  sex  and  death   •  At  every  0ck  we  collect  the  popula0on  of  the   en0re  world,  as  well  as  popula0on  of  males   and  females  

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Second  simula0on  

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Data  analysis   Popula0on   fluctuates  

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With  minor  tweaks  …   Popula0on  fluctua0ons   resul0ng  in  disaster  

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What  just  happened?   •  I  changed  a  parameter  -­‐  the  childbearing  age   •  Original   – CHILDBEARING_AGE  =  25..50   •  Changed   – CHILDBEARING_AGE  =  30..50   •  Does  it  happen  all  the  0me?  NO  -­‐  4  out  of  5   0mes  

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Looks  familiar?   •  Financial  crashes,  social  unrest  (Arab  Spring?),   animal  ex0nc0ons,  climate  change?   •  Simula0on  suggests  small  internal  factors  can   be  enough  to  trigger  crises  that  cannot  be   recovered    

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Things  are  NOT  as  stable   as  we  like  to  think  it  is  

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Natural  selec0on   •  A  central  concept  in  evolu0on   •  “Survival  of  the  fiRest”   •  Organisms  with  more  suitable  aRributes  are   more  likely  to  reproduce  and  pass  these   aRributes  to  the  next  genera0on   •  Over  0me  these  aRributes  become   more  prominent  

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Natural  selec0on  in  Utopia   •  Previously  all  roids  have  the  same  aRributes,  only   difference  is  maximum  lifespan  and  energy  level   •  In  this  simula0on,  we  add  2  new  aRributes   –  Metabolism   How  well  the  roid  converts  the  food  it  eats  into  energy  (higher   number  beRer)   –  Vision  range   How  far  away  it  can  see  food  (higher  number  beRer)   •  Roid  babies  inherit  these  2  aRributes  from  their   parents  

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Crossover  of  gene0c  aRributes   •  We  follow  very  simple  Mendelian  rules  for   crossover   •  Assume  the  father  has  the  genotype  (m,v)  and   the  mother  has  genotype  (M,V)   •  Possible  genotypes  of  baby  are  (m,v),  (m,V),   (M,v)  and  (M,V)   •  We  randomly  chose  1  of  these  4  possibili0es    

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Data  collec0on   •  We  want  to  find  out  how  the  metabolism  and   vision  range  aRributes  of  the  popula0on   changes  over  0me   •  At  every  0ck,  we  calculate  the  average   metabolism  and  vision  range  of  all  roids  that   are  alive  

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Third  simula0on  

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Natural  selec0on  in  ac0on!   Metabolism   improves  over   0me   Vision  range   improves  over   0me  

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What  did  we  just  see?   •  Natural  selec0on  -­‐  the  roids  with  the  beRer   aRributes  are  able  to  survive  longer  and   reproduce  with  similar  aRributes   •  Natural  selec0on  is  not  necessarily  a  straight   line  (vision  range  meanders  for  a  while)  

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Wrapup   •  Simula0ons  ≠  real  life   •  Conclusions  open  for  interpreta0on   •  Programming  as  tools  to  discover  the  world   around  us  

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Miscellaneous  stuff   •  Simula0on  –  Ruby,  Gosu   •  Analysis  –  Ruby,  Gruff   •  hRps://github.com/sausheong/utopia   •  [email protected]  -­‐  personal   •  [email protected]  -­‐  work