playbook.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import uuid\n",
    "import matplotlib.pyplot as plt\n",
    "import imageio\n",
    "from time import time\n",
    "from PyProbs import Probability as pr\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from gensim import *\n",
    "from gensim.Enviroment import SelectionCriterias\n",
    "import logging"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Runtime settings\n",
    "LOGGING_LEVEL=logging.INFO\n",
    "MULTITHREADING_NTHREADS=100\n",
    "ANIMATION_FPS=10\n",
    "\n",
    "# Simulation settings\n",
    "MAP_SIZE=20\n",
    "POPULATION_SIZE=100\n",
    "NUM_STEPS=10\n",
    "NUM_GENERATIONS=100\n",
    "\n",
    "# Genome settings\n",
    "GENE_SIZE=20\n",
    "NUM_INTERNAL_NEURON=3\n",
    "MUTATION_RATE=0.1\n",
    "\n",
    "# Selection criteria\n",
    "SELECTION_AREA_SIZE=0.2\n",
    "SELECTION_CRITERIA_TYPE=SelectionCriterias.BOTH_SIDE\n",
    "\n",
    "env = Enviroment.SimEnv(size=MAP_SIZE,\n",
    "                        population_size=POPULATION_SIZE, \n",
    "                        num_steps=NUM_STEPS, \n",
    "                        num_rounds=NUM_GENERATIONS,\n",
    "                        gene_size=GENE_SIZE, \n",
    "                        num_int_neuron=NUM_INTERNAL_NEURON, \n",
    "                        mutation_probability=MUTATION_RATE,\n",
    "                        criteria_type=SELECTION_CRITERIA_TYPE, \n",
    "                        selection_area_width_pct=SELECTION_AREA_SIZE, \n",
    "                        multithreading=MULTITHREADING_NTHREADS,\n",
    "                        animation_fps=ANIMATION_FPS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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