06-breadth-first-search.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Prohledávání do šířky (BFS)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline\n",
    "from search import parse_state, is_goal, actions, move\n",
    "from search import show_plan, visualize_search, log_search_step\n",
    "import solutions"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Variantou stromového prohledávní, které najde nejkraší cestu,\n",
    "je *prohledávání do šířky* (*Breadth-first search*, BFS).\n",
    "Při BFS využíváme jako okraj frontu, tedy kolekci typu *First-In First-Out* (FIFO), což je prostě seznam, v němž odebíráme z opačné strany, než na kterou přidáváme. Jako u běžné fronty v obchodě."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fronta v Pythonu"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deque(['a', 'b', 'c', 'd'])\n",
      "deque(['b', 'c', 'd'])\n",
      "deque(['c', 'd'])\n"
     ]
    }
   ],
   "source": [
    "from collections import deque\n",
    "queue = deque(['a', 'b', 'c'])  # 'a' na zacatku fronty, 'c' na konci\n",
    "queue.append('d')  # 'd' prisel na konec fronty\n",
    "print(queue)  # deque(['a', 'b', 'c', 'd'])\n",
    "queue.popleft()  # odchazi 'a'\n",
    "print(queue)  # deque(['b', 'c', 'd'])\n",
    "queue.popleft()  # odchazi 'b'\n",
    "print(queue)  # deque(['c', 'd'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## BFS krok za krokem\n",
    "\n",
    "Při použití fronty jako okraje dojde k průzkumu prvků v pořadí po vrstvách podle jejich vzdálenosti od počátečního stavu:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Explored: Fringe:              Plans:                 \n",
      "0: -      [c1]                 c1:''                  \n",
      "1: c1     [b2, d2]             + b2:l, d2:r           \n",
      "2: b2     [d2, a3, b3]         + a3:ll, b3:lf         \n",
      "3: d2     [a3, b3, d3, e3]     + d3:rf, e3:rr         \n",
      "4: a3     [b3, d3, e3, a4, b4] + a4:llf, b4:llr       \n",
      "5: b3     [d3, e3, a4, b4]                            \n",
      "6: d3     [e3, a4, b4, d4, e4] + d4:rff, e4:rfr       \n",
      "7: e3     [a4, b4, d4, e4]                            \n",
      "8: a4     [b4, d4, e4]                                \n"
     ]
    },
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f30d599d438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "state = parse_state(\n",
    "'| | |A| | |'\n",
    "'| | |A| | |'\n",
    "'| | |A| | |'\n",
    "'| | |S| | |')\n",
    "with visualize_search(state, text=True, interactive=False):\n",
    "    solutions.bfs(state)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Implementace\n",
    "\n",
    "<div class=\"alert alert-block alert-success\">\n",
    "<b>Úkol 6.1: Prohledávání do šířky</b><br/>\n",
    "Implementujte funkci <i>bfs(initial_state)</i>,\n",
    "která vrací nejkratší plán pro cestu z <i>initial_state</i> do cílového stavu\n",
    "nalezený pomocí prohledávání do šířky.\n",
    "\n",
    "<p>\n",
    "Tipy:\n",
    "<ul>\n",
    "<li>Použijte frontu pro ukládání stavů na okraji.</li>\n",
    "<li>\n",
    "Pro každý objevený stav si uložte jeho plán do slovníku (jako u DFS).\n",
    "</li>\n",
    "<li>\n",
    "Abyste zabránily opakovanému prozkoumávání stejných stavů,\n",
    "do kterých se lze dostat více cestami,\n",
    "přidávejte do fronty pouze ještě neobjevené stavy.\n",
    "Pro všechny objevené stavy máme nějaký plán,\n",
    "takže kontrola může vypadat takto:\n",
    "`if next_state not in plans: ...`.\n",
    "</li>\n",
    "</ul>\n",
    "</p>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f30d5907ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f30d59ae208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def bfs(initial_state):\n",
    "    queue = deque([initial_state])\n",
    "    plans = {initial_state: ''}\n",
    "    log_search_step(None, queue, plans)\n",
    "    while queue:\n",
    "        state = queue.popleft()\n",
    "        # TODO: Implementujte BFS.\n",
    "        log_search_step(state, queue, plans)\n",
    "\n",
    "state = parse_state(\n",
    "'| | |A| | |'\n",
    "'| | |A| |W|'\n",
    "'| | |A| | |'\n",
    "'| | |A|W| |'\n",
    "'| | |A| | |'\n",
    "'| | |S| | |')\n",
    "with visualize_search(state, interactive=False):\n",
    "    plan = solutions.bfs(state)  # Vzorove reseni.\n",
    "    #plan = bfs(state)  # Vase reseni:\n",
    "show_plan(state, plan)"
   ]
  },
  {
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   "metadata": {},
   "source": [
    "## Shrnutí\n",
    "\n",
    "<div class=\"alert alert-block alert-info\">\n",
    "<ul>\n",
    "<li>\n",
    "BFS je varianta stromového prohledávání, při kterém stavy z okraje\n",
    "vybíráme v pořadí FIFO (First In - First Out), tj.\n",
    "jako okraj používáme frontu.\n",
    "</li>\n",
    "<li>\n",
    "BFS prochází stavy v pořadí podle jejich vzdálenosti od počátečního stavu. Díky tomu najde zaručeně nejkratší řešení.\n",
    "</li>\n",
    "<li>\n",
    "BFS má typicky větší paměťové nároky než DFS.\n",
    "(Pokud je cíl v hloubce h, bude fronta obsahovat\n",
    "všechny stavy, do kterých se dá dostat h akcemi.)\n",
    "</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "Co ale s tím, když mají akce různou cenu? [07 - Prohledávání s cenou](./07-uniform-cost-search.ipynb)"
   ]
  }
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       "outputs": [
        {
         "data": {
          "image/png": 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          "text/plain": "<matplotlib.figure.Figure at 0x7f79c579d080>"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "c498d2d898084bf183a39fa2041a55c1": {
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      "model_name": "LayoutModel",
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     },
     "d69c017bc8514c5087260020f4c721f9": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
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     "d849d1d42f8a47b6bb239d06764f8e7f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
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     },
     "d891c1fc1b434fcb96ab17e8ed417343": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "children": [
        "IPY_MODEL_669b0b45dba54805b5aea4ce8603696e",
        "IPY_MODEL_518213d9c1d2402a9911687a20219837"
       ],
       "layout": "IPY_MODEL_7908f9d9f0b0467f884101ae8c41c6fe"
      }
     },
     "eaf3df9729424f62bd153ed332053b4f": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "eb64d4b5266b4f308a71321a0f84c51d": {
      "model_module": "@jupyter-widgets/controls",
      "model_module_version": "1.0.0",
      "model_name": "VBoxModel",
      "state": {
       "_dom_classes": [
        "widget-interact"
       ],
       "children": [
        "IPY_MODEL_a45e349f196b494cae977e6da5c9b838",
        "IPY_MODEL_54cc9d28c9fc4333bbaeb32c74262ea4"
       ],
       "layout": "IPY_MODEL_81580ee1350f44778e7bbf0d6c4789ce"
      }
     },
     "ebd5518599a945f7a54739b1d7b3ee39": {
      "model_module": "@jupyter-widgets/base",
      "model_module_version": "1.0.0",
      "model_name": "LayoutModel",
      "state": {}
     },
     "f08e779637d342469a88eab227c921ab": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_4714af76ab8f4325a720f661b4fb1688",
       "outputs": [
        {
         "data": {
          "image/png": 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          "text/plain": "<matplotlib.figure.Figure at 0x7f79c58c3cc0>"
         },
         "metadata": {},
         "output_type": "display_data"
        }
       ]
      }
     },
     "f5c27d07517d41f5a1fe52da5439231f": {
      "model_module": "@jupyter-widgets/output",
      "model_module_version": "1.0.0",
      "model_name": "OutputModel",
      "state": {
       "layout": "IPY_MODEL_6ca8dfea53214a97839304e3034221e5",
       "outputs": [
        {
         "data": {
          "image/png": 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