executable_br.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from scarsa_lambda_br import *\n",
    "\n",
    "import pickle"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/svg+xml": [
       "<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" version=\"1.2\" baseProfile=\"tiny\" viewBox=\"0 0 390 390\" width=\"390\" height=\"390\"><desc><pre>. . . . . . Q .\n",
       ". . . . K . . .\n",
       ". . . . . . . .\n",
       ". . . . . . . .\n",
       ". . k . . . . .\n",
       ". . . . . . . .\n",
       ". . . . . . . .\n",
       ". . . . . . . .</pre></desc><defs><g id=\"white-queen\" class=\"white queen\" fill=\"#fff\" fill-rule=\"evenodd\" stroke=\"#000\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M8 12a2 2 0 1 1-4 0 2 2 0 1 1 4 0zM24.5 7.5a2 2 0 1 1-4 0 2 2 0 1 1 4 0zM41 12a2 2 0 1 1-4 0 2 2 0 1 1 4 0zM16 8.5a2 2 0 1 1-4 0 2 2 0 1 1 4 0zM33 9a2 2 0 1 1-4 0 2 2 0 1 1 4 0z\" /><path d=\"M9 26c8.5-1.5 21-1.5 27 0l2-12-7 11V11l-5.5 13.5-3-15-3 15-5.5-14V25L7 14l2 12zM9 26c0 2 1.5 2 2.5 4 1 1.5 1 1 .5 3.5-1.5 1-1.5 2.5-1.5 2.5-1.5 1.5.5 2.5.5 2.5 6.5 1 16.5 1 23 0 0 0 1.5-1 0-2.5 0 0 .5-1.5-1-2.5-.5-2.5-.5-2 .5-3.5 1-2 2.5-2 2.5-4-8.5-1.5-18.5-1.5-27 0z\" stroke-linecap=\"butt\" /><path d=\"M11.5 30c3.5-1 18.5-1 22 0M12 33.5c6-1 15-1 21 0\" fill=\"none\" /></g><g id=\"white-king\" class=\"white king\" fill=\"none\" fill-rule=\"evenodd\" stroke=\"#000\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M22.5 11.63V6M20 8h5\" stroke-linejoin=\"miter\" /><path d=\"M22.5 25s4.5-7.5 3-10.5c0 0-1-2.5-3-2.5s-3 2.5-3 2.5c-1.5 3 3 10.5 3 10.5\" fill=\"#fff\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" /><path d=\"M11.5 37c5.5 3.5 15.5 3.5 21 0v-7s9-4.5 6-10.5c-4-6.5-13.5-3.5-16 4V27v-3.5c-3.5-7.5-13-10.5-16-4-3 6 5 10 5 10V37z\" fill=\"#fff\" /><path d=\"M11.5 30c5.5-3 15.5-3 21 0m-21 3.5c5.5-3 15.5-3 21 0m-21 3.5c5.5-3 15.5-3 21 0\" /></g><g id=\"black-king\" class=\"black king\" fill=\"none\" fill-rule=\"evenodd\" stroke=\"#000\" stroke-width=\"1.5\" stroke-linecap=\"round\" stroke-linejoin=\"round\"><path d=\"M22.5 11.63V6\" stroke-linejoin=\"miter\" /><path d=\"M22.5 25s4.5-7.5 3-10.5c0 0-1-2.5-3-2.5s-3 2.5-3 2.5c-1.5 3 3 10.5 3 10.5\" fill=\"#000\" stroke-linecap=\"butt\" stroke-linejoin=\"miter\" /><path d=\"M11.5 37c5.5 3.5 15.5 3.5 21 0v-7s9-4.5 6-10.5c-4-6.5-13.5-3.5-16 4V27v-3.5c-3.5-7.5-13-10.5-16-4-3 6 5 10 5 10V37z\" fill=\"#000\" /><path d=\"M20 8h5\" stroke-linejoin=\"miter\" /><path d=\"M32 29.5s8.5-4 6.03-9.65C34.15 14 25 18 22.5 24.5l.01 2.1-.01-2.1C20 18 9.906 14 6.997 19.85c-2.497 5.65 4.853 9 4.853 9M11.5 30c5.5-3 15.5-3 21 0m-21 3.5c5.5-3 15.5-3 21 0m-21 3.5c5.5-3 15.5-3 21 0\" stroke=\"#fff\" /></g></defs><rect x=\"0\" y=\"0\" width=\"390\" height=\"390\" fill=\"#212121\" /><g transform=\"translate(20, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M23.328 10.016q-1.742 0-2.414.398-.672.398-.672 1.36 0 .765.5 1.218.508.445 1.375.445 1.196 0 1.914-.843.727-.852.727-2.258v-.32zm2.867-.594v4.992h-1.437v-1.328q-.492.797-1.227 1.18-.734.375-1.797.375-1.343 0-2.14-.75-.79-.758-.79-2.024 0-1.476.985-2.226.992-.75 2.953-.75h2.016V8.75q0-.992-.656-1.531-.649-.547-1.829-.547-.75 0-1.46.18-.711.18-1.368.539V6.062q.79-.304 1.532-.453.742-.156 1.445-.156 1.898 0 2.836.984.937.985.937 2.985z\" /></g><g transform=\"translate(20, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M23.328 10.016q-1.742 0-2.414.398-.672.398-.672 1.36 0 .765.5 1.218.508.445 1.375.445 1.196 0 1.914-.843.727-.852.727-2.258v-.32zm2.867-.594v4.992h-1.437v-1.328q-.492.797-1.227 1.18-.734.375-1.797.375-1.343 0-2.14-.75-.79-.758-.79-2.024 0-1.476.985-2.226.992-.75 2.953-.75h2.016V8.75q0-.992-.656-1.531-.649-.547-1.829-.547-.75 0-1.46.18-.711.18-1.368.539V6.062q.79-.304 1.532-.453.742-.156 1.445-.156 1.898 0 2.836.984.937.985.937 2.985z\" /></g><g transform=\"translate(65, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.922 10.047q0-1.586-.656-2.485-.649-.906-1.79-.906-1.14 0-1.796.906-.649.899-.649 2.485 0 1.586.649 2.492.656.898 1.797.898 1.14 0 1.789-.898.656-.906.656-2.492zm-4.89-3.055q.452-.781 1.14-1.156.695-.383 1.656-.383 1.594 0 2.586 1.266 1 1.265 1 3.328 0 2.062-1 3.328-.992 1.266-2.586 1.266-.96 0-1.656-.375-.688-.383-1.14-1.164v1.312h-1.446V2.258h1.445z\" /></g><g transform=\"translate(65, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.922 10.047q0-1.586-.656-2.485-.649-.906-1.79-.906-1.14 0-1.796.906-.649.899-.649 2.485 0 1.586.649 2.492.656.898 1.797.898 1.14 0 1.789-.898.656-.906.656-2.492zm-4.89-3.055q.452-.781 1.14-1.156.695-.383 1.656-.383 1.594 0 2.586 1.266 1 1.265 1 3.328 0 2.062-1 3.328-.992 1.266-2.586 1.266-.96 0-1.656-.375-.688-.383-1.14-1.164v1.312h-1.446V2.258h1.445z\" /></g><g transform=\"translate(110, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M25.96 6v1.344q-.608-.336-1.226-.5-.609-.172-1.234-.172-1.398 0-2.172.89-.773.883-.773 2.485 0 1.601.773 2.492.774.883 2.172.883.625 0 1.234-.164.618-.172 1.227-.508v1.328q-.602.281-1.25.422-.64.14-1.367.14-1.977 0-3.14-1.242-1.165-1.242-1.165-3.351 0-2.14 1.172-3.367 1.18-1.227 3.227-1.227.664 0 1.296.14.633.134 1.227.407z\" /></g><g transform=\"translate(110, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M25.96 6v1.344q-.608-.336-1.226-.5-.609-.172-1.234-.172-1.398 0-2.172.89-.773.883-.773 2.485 0 1.601.773 2.492.774.883 2.172.883.625 0 1.234-.164.618-.172 1.227-.508v1.328q-.602.281-1.25.422-.64.14-1.367.14-1.977 0-3.14-1.242-1.165-1.242-1.165-3.351 0-2.14 1.172-3.367 1.18-1.227 3.227-1.227.664 0 1.296.14.633.134 1.227.407z\" /></g><g transform=\"translate(155, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.973 6.992V2.258h1.437v12.156h-1.437v-1.312q-.453.78-1.149 1.164-.687.375-1.656.375-1.586 0-2.586-1.266-.992-1.266-.992-3.328 0-2.063.992-3.328 1-1.266 2.586-1.266.969 0 1.656.383.696.375 1.149 1.156zm-4.899 3.055q0 1.586.649 2.492.656.898 1.797.898 1.14 0 1.796-.898.657-.906.657-2.492 0-1.586-.657-2.485-.656-.906-1.796-.906-1.141 0-1.797.906-.649.899-.649 2.485z\" /></g><g transform=\"translate(155, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.973 6.992V2.258h1.437v12.156h-1.437v-1.312q-.453.78-1.149 1.164-.687.375-1.656.375-1.586 0-2.586-1.266-.992-1.266-.992-3.328 0-2.063.992-3.328 1-1.266 2.586-1.266.969 0 1.656.383.696.375 1.149 1.156zm-4.899 3.055q0 1.586.649 2.492.656.898 1.797.898 1.14 0 1.796-.898.657-.906.657-2.492 0-1.586-.657-2.485-.656-.906-1.796-.906-1.141 0-1.797.906-.649.899-.649 2.485z\" /></g><g transform=\"translate(200, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M26.555 9.68v.703h-6.61q.094 1.484.89 2.265.806.774 2.235.774.828 0 1.602-.203.781-.203 1.547-.61v1.36q-.774.328-1.586.5-.813.172-1.649.172-2.093 0-3.32-1.22-1.219-1.218-1.219-3.296 0-2.148 1.157-3.406 1.164-1.266 3.132-1.266 1.766 0 2.79 1.14 1.03 1.134 1.03 3.087zm-1.438-.422q-.015-1.18-.664-1.883-.64-.703-1.703-.703-1.203 0-1.93.68-.718.68-.828 1.914z\" /></g><g transform=\"translate(200, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M26.555 9.68v.703h-6.61q.094 1.484.89 2.265.806.774 2.235.774.828 0 1.602-.203.781-.203 1.547-.61v1.36q-.774.328-1.586.5-.813.172-1.649.172-2.093 0-3.32-1.22-1.219-1.218-1.219-3.296 0-2.148 1.157-3.406 1.164-1.266 3.132-1.266 1.766 0 2.79 1.14 1.03 1.134 1.03 3.087zm-1.438-.422q-.015-1.18-.664-1.883-.64-.703-1.703-.703-1.203 0-1.93.68-.718.68-.828 1.914z\" /></g><g transform=\"translate(245, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M25.285 2.258v1.195H23.91q-.773 0-1.078.313-.297.312-.297 1.125v.773h2.367v1.117h-2.367v7.633H21.09V6.781h-1.375V5.664h1.375v-.61q0-1.46.68-2.124.68-.672 2.156-.672z\" /></g><g transform=\"translate(245, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M25.285 2.258v1.195H23.91q-.773 0-1.078.313-.297.312-.297 1.125v.773h2.367v1.117h-2.367v7.633H21.09V6.781h-1.375V5.664h1.375v-.61q0-1.46.68-2.124.68-.672 2.156-.672z\" /></g><g transform=\"translate(290, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.973 9.937q0-1.562-.649-2.421-.64-.86-1.804-.86-1.157 0-1.805.86-.64.859-.64 2.421 0 1.555.64 2.415.648.859 1.805.859 1.164 0 1.804-.86.649-.859.649-2.414zm1.437 3.391q0 2.234-.992 3.32-.992 1.094-3.04 1.094-.757 0-1.429-.117-.672-.11-1.304-.344v-1.398q.632.344 1.25.508.617.164 1.257.164 1.414 0 2.118-.743.703-.734.703-2.226v-.711q-.446.773-1.141 1.156-.695.383-1.664.383-1.61 0-2.594-1.227-.984-1.226-.984-3.25 0-2.03.984-3.257.985-1.227 2.594-1.227.969 0 1.664.383t1.14 1.156V5.664h1.438z\" /></g><g transform=\"translate(290, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M24.973 9.937q0-1.562-.649-2.421-.64-.86-1.804-.86-1.157 0-1.805.86-.64.859-.64 2.421 0 1.555.64 2.415.648.859 1.805.859 1.164 0 1.804-.86.649-.859.649-2.414zm1.437 3.391q0 2.234-.992 3.32-.992 1.094-3.04 1.094-.757 0-1.429-.117-.672-.11-1.304-.344v-1.398q.632.344 1.25.508.617.164 1.257.164 1.414 0 2.118-.743.703-.734.703-2.226v-.711q-.446.773-1.141 1.156-.695.383-1.664.383-1.61 0-2.594-1.227-.984-1.226-.984-3.25 0-2.03.984-3.257.985-1.227 2.594-1.227.969 0 1.664.383t1.14 1.156V5.664h1.438z\" /></g><g transform=\"translate(335, 0) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M26.164 9.133v5.281h-1.437V9.18q0-1.243-.485-1.86-.484-.617-1.453-.617-1.164 0-1.836.742-.672.742-.672 2.024v4.945h-1.445V2.258h1.445v4.765q.516-.789 1.211-1.18.703-.39 1.617-.39 1.508 0 2.282.938.773.93.773 2.742z\" /></g><g transform=\"translate(335, 375) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M26.164 9.133v5.281h-1.437V9.18q0-1.243-.485-1.86-.484-.617-1.453-.617-1.164 0-1.836.742-.672.742-.672 2.024v4.945h-1.445V2.258h1.445v4.765q.516-.789 1.211-1.18.703-.39 1.617-.39 1.508 0 2.282.938.773.93.773 2.742z\" /></g><g transform=\"translate(0, 335) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.754 26.996h2.578v-8.898l-2.805.562v-1.437l2.79-.563h1.578v10.336h2.578v1.328h-6.72z\" /></g><g transform=\"translate(375, 335) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.754 26.996h2.578v-8.898l-2.805.562v-1.437l2.79-.563h1.578v10.336h2.578v1.328h-6.72z\" /></g><g transform=\"translate(0, 290) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M8.195 26.996h5.508v1.328H6.297v-1.328q.898-.93 2.445-2.492 1.555-1.57 1.953-2.024.758-.851 1.055-1.437.305-.594.305-1.164 0-.93-.657-1.516-.648-.586-1.695-.586-.742 0-1.57.258-.82.258-1.758.781v-1.593q.953-.383 1.781-.578.828-.196 1.516-.196 1.812 0 2.89.906 1.079.907 1.079 2.422 0 .72-.274 1.368-.265.64-.976 1.515-.196.227-1.243 1.313-1.046 1.078-2.953 3.023z\" /></g><g transform=\"translate(375, 290) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M8.195 26.996h5.508v1.328H6.297v-1.328q.898-.93 2.445-2.492 1.555-1.57 1.953-2.024.758-.851 1.055-1.437.305-.594.305-1.164 0-.93-.657-1.516-.648-.586-1.695-.586-.742 0-1.57.258-.82.258-1.758.781v-1.593q.953-.383 1.781-.578.828-.196 1.516-.196 1.812 0 2.89.906 1.079.907 1.079 2.422 0 .72-.274 1.368-.265.64-.976 1.515-.196.227-1.243 1.313-1.046 1.078-2.953 3.023z\" /></g><g transform=\"translate(0, 245) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M11.434 22.035q1.132.242 1.765 1.008.64.766.64 1.89 0 1.727-1.187 2.672-1.187.946-3.375.946-.734 0-1.515-.149-.774-.14-1.602-.43V26.45q.656.383 1.438.578.78.196 1.632.196 1.485 0 2.258-.586.782-.586.782-1.703 0-1.032-.727-1.61-.719-.586-2.008-.586h-1.36v-1.297h1.423q1.164 0 1.78-.46.618-.47.618-1.344 0-.899-.64-1.375-.633-.485-1.82-.485-.65 0-1.391.141-.743.14-1.633.437V16.95q.898-.25 1.68-.375.788-.125 1.484-.125 1.797 0 2.844.82 1.046.813 1.046 2.204 0 .968-.554 1.64-.555.664-1.578.922z\" /></g><g transform=\"translate(375, 245) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M11.434 22.035q1.132.242 1.765 1.008.64.766.64 1.89 0 1.727-1.187 2.672-1.187.946-3.375.946-.734 0-1.515-.149-.774-.14-1.602-.43V26.45q.656.383 1.438.578.78.196 1.632.196 1.485 0 2.258-.586.782-.586.782-1.703 0-1.032-.727-1.61-.719-.586-2.008-.586h-1.36v-1.297h1.423q1.164 0 1.78-.46.618-.47.618-1.344 0-.899-.64-1.375-.633-.485-1.82-.485-.65 0-1.391.141-.743.14-1.633.437V16.95q.898-.25 1.68-.375.788-.125 1.484-.125 1.797 0 2.844.82 1.046.813 1.046 2.204 0 .968-.554 1.64-.555.664-1.578.922z\" /></g><g transform=\"translate(0, 200) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M11.016 18.035L7.03 24.262h3.985zm-.414-1.375h1.984v7.602h1.664v1.312h-1.664v2.75h-1.57v-2.75H5.75v-1.523z\" /></g><g transform=\"translate(375, 200) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M11.016 18.035L7.03 24.262h3.985zm-.414-1.375h1.984v7.602h1.664v1.312h-1.664v2.75h-1.57v-2.75H5.75v-1.523z\" /></g><g transform=\"translate(0, 155) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.719 16.66h6.195v1.328h-4.75v2.86q.344-.118.688-.172.343-.063.687-.063 1.953 0 3.094 1.07 1.14 1.07 1.14 2.899 0 1.883-1.171 2.93-1.172 1.039-3.305 1.039-.735 0-1.5-.125-.758-.125-1.57-.375v-1.586q.703.383 1.453.57.75.188 1.586.188 1.351 0 2.14-.711.79-.711.79-1.93 0-1.219-.79-1.93-.789-.71-2.14-.71-.633 0-1.266.14-.625.14-1.281.438z\" /></g><g transform=\"translate(375, 155) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.719 16.66h6.195v1.328h-4.75v2.86q.344-.118.688-.172.343-.063.687-.063 1.953 0 3.094 1.07 1.14 1.07 1.14 2.899 0 1.883-1.171 2.93-1.172 1.039-3.305 1.039-.735 0-1.5-.125-.758-.125-1.57-.375v-1.586q.703.383 1.453.57.75.188 1.586.188 1.351 0 2.14-.711.79-.711.79-1.93 0-1.219-.79-1.93-.789-.71-2.14-.71-.633 0-1.266.14-.625.14-1.281.438z\" /></g><g transform=\"translate(0, 110) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M10.137 21.863q-1.063 0-1.688.727-.617.726-.617 1.992 0 1.258.617 1.992.625.727 1.688.727 1.062 0 1.68-.727.624-.734.624-1.992 0-1.266-.625-1.992-.617-.727-1.68-.727zm3.133-4.945v1.437q-.594-.28-1.204-.43-.601-.148-1.195-.148-1.562 0-2.39 1.055-.82 1.055-.938 3.188.46-.68 1.156-1.04.696-.367 1.531-.367 1.758 0 2.774 1.07 1.023 1.063 1.023 2.899 0 1.797-1.062 2.883-1.063 1.086-2.828 1.086-2.024 0-3.094-1.547-1.07-1.555-1.07-4.5 0-2.766 1.312-4.406 1.313-1.649 3.524-1.649.593 0 1.195.117.61.118 1.266.352z\" /></g><g transform=\"translate(375, 110) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M10.137 21.863q-1.063 0-1.688.727-.617.726-.617 1.992 0 1.258.617 1.992.625.727 1.688.727 1.062 0 1.68-.727.624-.734.624-1.992 0-1.266-.625-1.992-.617-.727-1.68-.727zm3.133-4.945v1.437q-.594-.28-1.204-.43-.601-.148-1.195-.148-1.562 0-2.39 1.055-.82 1.055-.938 3.188.46-.68 1.156-1.04.696-.367 1.531-.367 1.758 0 2.774 1.07 1.023 1.063 1.023 2.899 0 1.797-1.062 2.883-1.063 1.086-2.828 1.086-2.024 0-3.094-1.547-1.07-1.555-1.07-4.5 0-2.766 1.312-4.406 1.313-1.649 3.524-1.649.593 0 1.195.117.61.118 1.266.352z\" /></g><g transform=\"translate(0, 65) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.25 16.66h7.5v.672L9.516 28.324H7.867l3.985-10.336H6.25z\" /></g><g transform=\"translate(375, 65) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M6.25 16.66h7.5v.672L9.516 28.324H7.867l3.985-10.336H6.25z\" /></g><g transform=\"translate(0, 20) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M10 22.785q-1.125 0-1.773.602-.641.601-.641 1.656t.64 1.656q.649.602 1.774.602t1.773-.602q.649-.61.649-1.656 0-1.055-.649-1.656-.64-.602-1.773-.602zm-1.578-.672q-1.016-.25-1.586-.945-.563-.695-.563-1.695 0-1.399.993-2.211 1-.813 2.734-.813 1.742 0 2.734.813.993.812.993 2.21 0 1-.57 1.696-.563.695-1.571.945 1.14.266 1.773 1.04.641.773.641 1.89 0 1.695-1.04 2.602-1.03.906-2.96.906t-2.969-.906Q6 26.738 6 25.043q0-1.117.64-1.89.641-.774 1.782-1.04zm-.578-2.492q0 .906.562 1.414.57.508 1.594.508 1.016 0 1.586-.508.578-.508.578-1.414 0-.906-.578-1.414-.57-.508-1.586-.508-1.023 0-1.594.508-.562.508-.562 1.414z\" /></g><g transform=\"translate(375, 20) scale(0.75, 0.75)\" fill=\"#e5e5e5\" stroke=\"#e5e5e5\"><path d=\"M10 22.785q-1.125 0-1.773.602-.641.601-.641 1.656t.64 1.656q.649.602 1.774.602t1.773-.602q.649-.61.649-1.656 0-1.055-.649-1.656-.64-.602-1.773-.602zm-1.578-.672q-1.016-.25-1.586-.945-.563-.695-.563-1.695 0-1.399.993-2.211 1-.813 2.734-.813 1.742 0 2.734.813.993.812.993 2.21 0 1-.57 1.696-.563.695-1.571.945 1.14.266 1.773 1.04.641.773.641 1.89 0 1.695-1.04 2.602-1.03.906-2.96.906t-2.969-.906Q6 26.738 6 25.043q0-1.117.64-1.89.641-.774 1.782-1.04zm-.578-2.492q0 .906.562 1.414.57.508 1.594.508 1.016 0 1.586-.508.578-.508.578-1.414 0-.906-.578-1.414-.57-.508-1.586-.508-1.023 0-1.594.508-.562.508-.562 1.414z\" /></g><rect x=\"15\" y=\"330\" width=\"45\" height=\"45\" class=\"square dark a1\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"60\" y=\"330\" width=\"45\" height=\"45\" class=\"square light b1\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"105\" y=\"330\" width=\"45\" height=\"45\" class=\"square dark c1\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"150\" y=\"330\" width=\"45\" height=\"45\" class=\"square light d1\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"195\" y=\"330\" width=\"45\" height=\"45\" class=\"square dark e1\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"240\" y=\"330\" width=\"45\" height=\"45\" class=\"square light f1\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"285\" y=\"330\" width=\"45\" height=\"45\" class=\"square dark g1\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"330\" y=\"330\" width=\"45\" height=\"45\" class=\"square light h1\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"15\" y=\"285\" width=\"45\" height=\"45\" class=\"square light a2\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"60\" y=\"285\" width=\"45\" height=\"45\" class=\"square dark b2\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"105\" y=\"285\" width=\"45\" height=\"45\" class=\"square light c2\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"150\" y=\"285\" width=\"45\" height=\"45\" class=\"square dark d2\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"195\" y=\"285\" width=\"45\" height=\"45\" class=\"square light e2\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"240\" y=\"285\" width=\"45\" height=\"45\" class=\"square dark f2\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"285\" y=\"285\" width=\"45\" height=\"45\" class=\"square light g2\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"330\" y=\"285\" width=\"45\" height=\"45\" class=\"square dark h2\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"15\" y=\"240\" width=\"45\" height=\"45\" class=\"square dark a3\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"60\" y=\"240\" width=\"45\" height=\"45\" class=\"square light b3\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"105\" y=\"240\" width=\"45\" height=\"45\" class=\"square dark c3\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"150\" y=\"240\" width=\"45\" height=\"45\" class=\"square light d3\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"195\" y=\"240\" width=\"45\" height=\"45\" class=\"square dark e3\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"240\" y=\"240\" width=\"45\" height=\"45\" class=\"square light f3\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"285\" y=\"240\" width=\"45\" height=\"45\" class=\"square dark g3\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"330\" y=\"240\" width=\"45\" height=\"45\" class=\"square light h3\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"15\" y=\"195\" width=\"45\" height=\"45\" class=\"square light a4\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"60\" y=\"195\" width=\"45\" height=\"45\" class=\"square dark b4\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"105\" y=\"195\" width=\"45\" height=\"45\" class=\"square light c4\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"150\" y=\"195\" width=\"45\" height=\"45\" class=\"square dark d4\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"195\" y=\"195\" width=\"45\" height=\"45\" class=\"square light e4\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"240\" y=\"195\" width=\"45\" height=\"45\" class=\"square dark f4\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"285\" y=\"195\" width=\"45\" height=\"45\" class=\"square light g4\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"330\" y=\"195\" width=\"45\" height=\"45\" class=\"square dark h4\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"15\" y=\"150\" width=\"45\" height=\"45\" class=\"square dark a5\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"60\" y=\"150\" width=\"45\" height=\"45\" class=\"square light b5\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"105\" y=\"150\" width=\"45\" height=\"45\" class=\"square dark c5\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"150\" y=\"150\" width=\"45\" height=\"45\" class=\"square light d5\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"195\" y=\"150\" width=\"45\" height=\"45\" class=\"square dark e5\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"240\" y=\"150\" width=\"45\" height=\"45\" class=\"square light f5\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"285\" y=\"150\" width=\"45\" height=\"45\" class=\"square dark g5\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"330\" y=\"150\" width=\"45\" height=\"45\" class=\"square light h5\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"15\" y=\"105\" width=\"45\" height=\"45\" class=\"square light a6\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"60\" y=\"105\" width=\"45\" height=\"45\" class=\"square dark b6\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"105\" y=\"105\" width=\"45\" height=\"45\" class=\"square light c6\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"150\" y=\"105\" width=\"45\" height=\"45\" class=\"square dark d6\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"195\" y=\"105\" width=\"45\" height=\"45\" class=\"square light e6\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"240\" y=\"105\" width=\"45\" height=\"45\" class=\"square dark f6\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"285\" y=\"105\" width=\"45\" height=\"45\" class=\"square light g6\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"330\" y=\"105\" width=\"45\" height=\"45\" class=\"square dark h6\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"15\" y=\"60\" width=\"45\" height=\"45\" class=\"square dark a7\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"60\" y=\"60\" width=\"45\" height=\"45\" class=\"square light b7\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"105\" y=\"60\" width=\"45\" height=\"45\" class=\"square dark c7\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"150\" y=\"60\" width=\"45\" height=\"45\" class=\"square light d7\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"195\" y=\"60\" width=\"45\" height=\"45\" class=\"square dark e7\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"240\" y=\"60\" width=\"45\" height=\"45\" class=\"square light f7\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"285\" y=\"60\" width=\"45\" height=\"45\" class=\"square dark g7\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"330\" y=\"60\" width=\"45\" height=\"45\" class=\"square light h7\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"15\" y=\"15\" width=\"45\" height=\"45\" class=\"square light a8\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"60\" y=\"15\" width=\"45\" height=\"45\" class=\"square dark b8\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"105\" y=\"15\" width=\"45\" height=\"45\" class=\"square light c8\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"150\" y=\"15\" width=\"45\" height=\"45\" class=\"square dark d8\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"195\" y=\"15\" width=\"45\" height=\"45\" class=\"square light e8\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"240\" y=\"15\" width=\"45\" height=\"45\" class=\"square dark f8\" stroke=\"none\" fill=\"#d18b47\" /><rect x=\"285\" y=\"15\" width=\"45\" height=\"45\" class=\"square light g8\" stroke=\"none\" fill=\"#ffce9e\" /><rect x=\"330\" y=\"15\" width=\"45\" height=\"45\" class=\"square dark h8\" stroke=\"none\" fill=\"#d18b47\" /><use href=\"#black-king\" xlink:href=\"#black-king\" transform=\"translate(105, 195)\" /><use href=\"#white-king\" xlink:href=\"#white-king\" transform=\"translate(195, 60)\" /><use href=\"#white-queen\" xlink:href=\"#white-queen\" transform=\"translate(285, 15)\" /></svg>"
      ],
      "text/plain": [
       "Board('6Q1/4K3/8/8/2k5/8/8/8 w - - 0 1')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "L_start = np.array([[2,4,5],[6,4,2]])\n",
    "\n",
    "Q, N, E, trend_results = scarsa_lambda(L_start, num_games = 1000, num_turns=20)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "trend_plot(trend_results)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Save the \"trained model\"\n",
    "for keys in Q:\n",
    "    Q[keys] = dict(Q[keys])\n",
    "Q = dict(Q)\n",
    "\n",
    "N = dict(N)\n",
    "\n",
    "\n",
    "with open('Q_s_20t_1000g.pickle', 'wb') as handle:\n",
    "    pickle.dump(Q, handle, protocol=pickle.HIGHEST_PROTOCOL)\n",
    "with open('N_s_20t_1000g.pickle', 'wb') as handle:\n",
    "    pickle.dump(N, handle, protocol=pickle.HIGHEST_PROTOCOL)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Total percentage of wins: 56.7 %\n",
      "Percentage of wins excluding the first 100 games: 63.0 %\n",
      "Percentage of wins excluding the first 200 games: 70.875 %\n",
      "Percentage of wins excluding the first 300 games: 81.0 %\n",
      "Percentage of wins excluding the first 400 games: 93.333 %\n",
      "Percentage of wins excluding the first 500 games: 98.0 %\n",
      "Percentage of wins excluding the first 600 games: 98.0 %\n",
      "Percentage of wins excluding the first 700 games: 97.667 %\n",
      "Percentage of wins excluding the first 800 games: 98.5 %\n",
      "Percentage of wins excluding the first 900 games: 98.0 %\n"
     ]
    }
   ],
   "source": [
    "# Count the percentage of wins:\n",
    "# --> learnedperc: percentage of wins excluding the first n-games of training.\n",
    "\n",
    "vals = trend_results #trend list\n",
    "df = pd.DataFrame(data=vals, columns=['Value'])\n",
    "df['difference'] = df.diff()\n",
    "learnlist = []\n",
    "\n",
    "for i in range(0,10):\n",
    "    n = i*100 #define the threshold after which calculate the percentage of wins.\n",
    "    count1 = 0\n",
    "    count2 = 0\n",
    "    for i in range(1, len(trend_results)): \n",
    "        if df.iloc[i, 1] == 1: \n",
    "            count1 += 1\n",
    "        if df.iloc[i, 1] == 1 and i > n: \n",
    "            count2 += 1\n",
    "    #totPerc = round(count1*100 / len(trend_results), 3)\n",
    "    learnedPerc = round(count2*100 / (len(trend_results)-n), 3)\n",
    "    learnlist.append(learnedPerc)\n",
    "\n",
    "    #print(\"Total percentage of wins:\", totPerc, \"%\", \"\\nPercentage of wins excluding the first\", n, \"games:\", learnedPerc, \"%\")\n",
    "    if n == 0: \n",
    "        print(\"Total percentage of wins:\", learnedPerc, \"%\")\n",
    "    else: \n",
    "        print(\"Percentage of wins excluding the first\", n, \"games:\", learnedPerc, \"%\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'percentage of wins')"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(learnlist, color = 'black', )\n",
    "plt.title(\"Wins percentage\")\n",
    "plt.xlabel(\"number of games excluded\")\n",
    "plt.ylabel(\"percentage of wins\")\n"
   ]
  }
 ],
 "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": "3.10.7"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "67e0cbc25fa4f5baaacba1240f401bc655b640f8e15cfc935dfee2e63491bdf4"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}