trying some simple simulations from The Selfish Gene

README

author: Jeremy Banks <[email protected]>
license: MIT (do what you want but give attribution)

I'm currently reading The Selfish Gene by Richard Dawkins. On page 185
(of ISBN 9780199291151) he mentions a computer simulation he ran to
test a theory. It sounded interesting and not too complicated, so I
decided to attempt to replicate it.

Currently, I am failing rather badly.

example.out

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simulation.py

#!/usr/bin/env python3.1
import sys
from time import time, sleep
from random import random, randint, randrange, choice as randchoice

class Individual(object):
    GROOMEE_POINTS =  10
    GROOMER_POINTS = -1
    
    def __init__(self):
        self.score = 0
    
    def request_grooming(self, other):
        if other.will_groom(self):
            self.score += self.GROOMEE_POINTS
            other.score += self.GROOMER_POINTS

class Sucker(Individual):
    """Suckers will always groom others."""
    symbol = "s"
    
    def will_groom(self, other):
        return True

class Cheat(Individual):
    """Cheats will never groom others."""
    symbol = "C"
    
    def will_groom(self, other):
        return False

class Grudger(Individual):
    """Grudgers will groom others who have not previously failed to reciprocate."""
    symbol = "g"
    
    def __init__(self):
        self.score = 0        
        self.have_groomed = set()
        self.known_cheaters = set()
    
    def request_grooming(self, other):
        if other.will_groom(self):
            self.score += self.GROOMEE_POINTS
            other.score += self.GROOMER_POINTS
        elif other in self.have_groomed:
            self.known_cheaters.add(other)
    
    def will_groom(self, other):
        if other not in self.known_cheaters:
            self.have_groomed.add(self)
            return True
        else:
            return False
    
def loop(f, while_=None, speed_limit=None):
    latest = while_
    if speed_limit:
        last_start = 0
    
    while latest == while_:
        if speed_limit:
            remaining = last_start + speed_limit - time()
            if remaining >= 0:
                sleep(remaining)
            last_start = time()
        latest = f()

    return latest

def main():
    grooms_per_generation = 5000
    death_rate = .5
    
    population = ( [ Cheat()   for _ in range(  5) ]
                 + [ Sucker()  for _ in range(  0) ]
                 + [ Grudger() for _ in range(175) ] )
    
    def tick():
        for _ in range(grooms_per_generation):
            a = b = randchoice(population)
            while b is a:
                b = randchoice(population)
            a.request_grooming(b)

        population.sort(key=lambda individual: individual.score)

        for _ in range(int(len(population) * death_rate)):
            dead_index = int( (random() * len(population)) ** 3
                              / len(population) ** 2)
            population[dead_index] = type(randchoice(population))()
        
        population.sort(key=lambda individual: individual.symbol)
        
        for individual in population:
            individual.score = 0
            sys.stdout.write(individual.symbol)

        sys.stdout.write("\n")

        if all(type(i) == type(population[0]) for i in population):
            # stop if population is homogenious
            return True
    
    loop(tick)

if __name__ == "__main__":
    sys.exit(main(*sys.argv[1:]))