{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "## Group selection model" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "This is a simple model of the evolution of cooperativeness by group selection.\n", "There are many existing models of group selection, but this one is particularly minimalist. There are no conflicts between groups, or exogenous events causing the extinction of particular groups. I simply assume that the population is divided into small groups, with a small rate of migration between groups.\n", "\n", "### mechanism\n", "\n", "Agents live in an archipelago of $k$ islands. Agents play games exclusively with agents living on their own island, and their offspring are born on the same island as the parent. However, after birth, an offspring may migrate to another island, with a probability determined by the migration rate. An agent who migrates simply moves to a randomly selected other island.\n", "\n", "The overall population size $N$ remains constant; however, the population of a given island can grow or decrease in size, given how many Cooperators and Defectors live on that island. Islands with a larger proportion of Cooperators grow at a faster rate, but within an island, Defectors tend to have more offspring. \n", "\n", "Concretely, every generation, agents within a group are randomly paired with one another to play a donation game. Then all agents reproduce as a function of their fitness and die. In the donation game, player 1 can 'Cooperate', i.e. pay a cost of 𝑐 to give a benefit 𝑏 to player 2, or 'Defect' (in which case nothing happens). Player 2 is a passive recipient. Groups with many cooperators tend to grow at a faster rate because, given $b > c$, members of a group with many cooperators have higher fitness. However, within a group, defectors avoid paying the cost of cooperation and so they are better off.\n", "\n", "### dynamics\n", "\n", "Try varying the migration rate to see what happens.\n", "\n", "When migration is impossible (i.e. agents remain stuck on their island of birth), Defection eventually prevails. This is because even in an island where everyone is a Cooperator, genetic mutation will inevitably introduce a Defector, whose malevolent gene will eventually take over the whole island.\n", "\n", "With a small migration rate, cooperation can evolve and remain stable. This is because in an island about to be overtaken by defectors, a few cooperators can migrate to an empty island to start things afresh. This maintains an overall positive assortment between cooperators.\n", "\n", "When the migration rate is too high, however, defectors take over, because a high rate of migration destroys the positive assortment between cooperators that is necessary to maintain cooperation.\n", "\n", "### how can cooperation be successful in this model?\n", "\n", "Under the right set of parameters, cooperation can evolve. The reason is that when the population is structured in small groups, sometimes by chance there will be groups with more cooperators than others. When that is the case, then on average cooperators meet other cooperators at an above-chance rate (where the above-chance rate is defined as would happen if the population was not structured into groups). Such positive assortment between cooperators makes cooperation evolutionarily successful. With the right migration rate, this positive assortment between cooperators can be self-perpetuating, leading to long-lasting cooperation. " ] }, { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [], "source": [ "import matplotlib.pyplot as plt" ] }, { "cell_type": "code", "execution_count": 2, "metadata": {}, "outputs": [], "source": [ "import numpy as np" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### General parameters of the model" ] }, { "cell_type": "code", "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "#number of groups\n", "k = 10\n", "\n", "#size of a group\n", "n = 20\n", "\n", "#population size\n", "N = n * k\n", "\n", "#number of generations\n", "g = 700\n", "\n", "#mutation rate\n", "mu = .01\n", "\n", "#migration rate\n", "migration_rate = 0.02\n", "\n", "#initial fitness\n", "initial_fitness = 10\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Specific game parameters" ] }, { "cell_type": "code", "execution_count": 4, "metadata": {}, "outputs": [], "source": [ "#cost and benefit in the DG\n", "b = 8\n", "c = -1\n", "\n", "\n", "#the strategy space\n", "strategy_space = [\"C\", \"D\"]\n", "\n", "\n", "#initial_strategy\n", "initial_strategy = \"D\"\n", "\n", "#does assortment depend on group membership, or is it random?\n", "#(the default is 'random_assortment = False'. Try activating randon assortment to see if altruism is still possible)\n", "random_assortment = False" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Define the \"agent\" class" ] }, { "cell_type": "code", "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "\n", "\n", "class agent:\n", " def __init__(self, name, group, strategy, fitness):\n", " self.name = name\n", " self.group = group\n", " self.strategy = strategy\n", " self.fitness = fitness\n", " \n", " def mutate(self):\n", " self.strategy=np.random.choice(strategy_space)\n", " \n", " def migrate(self):\n", " self.group = np.random.choice(range(k))\n", " \n", " def add_to_fitness(self, increment):\n", " self.fitness += increment\n", "\n", " def change_group(self, new_group):\n", " self.group = new_group\n", " " ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Some key functions\n" ] }, { "cell_type": "code", "execution_count": 6, "metadata": {}, "outputs": [], "source": [ "#the successor function\n", "#used to pair an element in an array with its successor in that array,\n", "#where the successor is either the next element,\n", "#or the 0th element, if the focal element is the last element in the array\n", "\n", "def successor(current, total):\n", " if current < total:\n", " return current + 1\n", " if current == total:\n", " return 0\n", " " ] }, { "cell_type": "code", "execution_count": 7, "metadata": {}, "outputs": [], "source": [ "#generate the initial population\n", "def initialize():\n", " #note that what we are doing with the second argument of the agent function\n", " #(which gives the group index of the agent we are creating):\n", " #we make it so that the n first agents we create belong to group 0, the next n agents belong to group 1, and so on\n", " return([agent(i, int(np.floor(i/n)), initial_strategy, initial_fitness) for i in range(N)])" ] }, { "cell_type": "code", "execution_count": 8, "metadata": {}, "outputs": [], "source": [ "#a handy function if we want to look at our population\n", "def print_pop():\n", " for i in range(N):\n", " print(pop[i].name, pop[i].group)\n", " \n" ] }, { "cell_type": "code", "execution_count": 9, "metadata": { "scrolled": true }, "outputs": [], "source": [ "#the function to compute average cooperativeness\n", "\n", "def average_X(X):\n", " return len([i for i in pop if i.strategy == X])/N" ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "scrolled": true }, "outputs": [], "source": [ "#put agents into pairs and have them play a game\n", "\n", "def games():\n", "\n", " \n", " arena = [[] for j in range(k)]\n", " \n", " for i in range(N):\n", " group_index = pop[i].group\n", " arena[group_index].append(i) \n", "\n", " #cycle through groups \n", " for j in range(k):\n", " #if there is more than one agent in the group\n", " if len(arena[j])>1:\n", " #shuffle the group\n", " np.random.shuffle(arena[j])\n", " #make agents in the group play games with one another\n", " for i in range(len(arena[j])):\n", " index_player1 = i\n", " index_player2 = successor(i, len(arena[j])-1)\n", " player1 = arena[j][index_player1]\n", " player2 = arena[j][index_player2]\n", " if (index_player1 != index_player2):\n", " DG(player1, player2)\n", "\n" ] }, { "cell_type": "code", "execution_count": 11, "metadata": {}, "outputs": [], "source": [ "#run games, in the assumption of random assortment\n", "#i.e., assortment is not a function of group membership\n", "def random_games():\n", " arena = list(range(N))\n", " np.random.shuffle(arena)\n", "\n", " for i in arena:\n", " if i % 2 == 0:\n", " DG(i, i+1)" ] }, { "cell_type": "code", "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "#the Donation Game\n", "\n", "def DG(player1, player2):\n", " player1_strat = pop[player1].strategy\n", " player2_strat = pop[player2].strategy\n", " \n", " if player1_strat == \"C\":\n", " pop[player2].add_to_fitness(b)\n", " pop[player1].add_to_fitness(c)\n", " \n", " \n", " \n" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "scrolled": false }, "outputs": [], "source": [ "#the selection function and its building blocks\n", "\n", "#standardize fitness so that agents with lowest fitness have fitness 1\n", "def standardization():\n", " \n", " min_fitness = min([i.fitness for i in pop])\n", " for i in range(N):\n", " pop[i].fitness += (1 - min_fitness)\n", "\n", "#each agent gets to put its name in a hat w times, where w is its fitness\n", "def lottery_prep():\n", " hat = []\n", " for i in range(N):\n", " for j in range(pop[i].fitness):\n", " hat.append(pop[i].name)\n", " return hat\n", "\n", "#create the next generation by drawing the name of the parents from the hat\n", "def reproduction(hat):\n", " temporary_pop=[]\n", " for i in range(N):\n", " name_drawn = np.random.choice(hat)\n", " hereditary_package = [pop[name_drawn].group, pop[name_drawn].strategy]\n", " temporary_pop.append(agent(i, hereditary_package[0], hereditary_package[1], initial_fitness))\n", "\n", " pop.clear()\n", " for i in range(N):\n", " pop.append(temporary_pop[i])\n", "\n", " \n", "\n", "\n", "#the selection function\n", "\n", "def selection():\n", "\n", " standardization()\n", " hat=lottery_prep()\n", " reproduction(hat)\n", "\n", "\n" ] }, { "cell_type": "code", "execution_count": 14, "metadata": {}, "outputs": [], "source": [ "def migration():\n", " for i in range(N):\n", " if (np.random.uniform() < migration_rate):\n", " pop[i].migrate()" ] }, { "cell_type": "code", "execution_count": 15, "metadata": {}, "outputs": [], "source": [ "def mutation():\n", " for i in range(N):\n", " if (np.random.uniform() < mu):\n", " pop[i].mutate()" ] }, { "cell_type": "code", "execution_count": 16, "metadata": {}, "outputs": [], "source": [ "def group_size(group):\n", " return len([i for i in range(N) if pop[i].group == group])\n", "\n", "\n", "#the repopulate function (Currently not implemented)\n", "#if an island is empty at the end of the reproduction phase, a randomly chosen\n", "#member of the population migrates there\n", "def repopulate():\n", " for j in range(k):\n", " if group_size(j) == 0:\n", " index = np.random.choice(range(N))\n", " pop[index].change_group(j)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Run the model and plot the dynamics" ] }, { "cell_type": "code", "execution_count": 17, "metadata": { "scrolled": false }, "outputs": [ { "data": { "text/plain": [ "(0, 1.05)" ] }, "execution_count": 17, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": { "needs_background": "light" }, "output_type": "display_data" } ], "source": [ "#this array records average Cooperativeness across a run\n", "Average_coop = []\n", "Average_d = []\n", "\n", "\n", "#create initial population\n", "pop = initialize()\n", "\n", "#run the model for g generations\n", "for i in range(g):\n", " if random_assortment == False:\n", " games()\n", " if random_assortment == True:\n", " random_games()\n", " selection()\n", " mutation()\n", " migration()\n", " Average_coop.append(average_X(\"C\"))\n", " Average_d.append(average_X(\"D\"))\n", "\n", "#plot results \n", "plt.figure( figsize=( 15, 8 ) )\n", "\n", "plt.title('Simulated Evolution of cooperativeness')\n", "\n", "plt.ylabel('Cooperativeness')\n", "plt.xlabel('Generation')\n", "plt.plot(Average_coop)\n", "plt.plot(Average_d, color = \"orange\")\n", "plt.ylim(0,1.05)\n", "\n" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "### Legend\n", "\n", "Blue = frequency of helpers\n", "\n", "Orange = frequency of cheaters" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.7.6" } }, "nbformat": 4, "nbformat_minor": 4 }