Untitled1.ipynb

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       "<h2></h2>\n",
       "\n",
       "<div class=\"highlight\"><pre><span></span><span class=\"k\">class</span> <span class=\"nc\">Agent</span><span class=\"p\">(</span><span class=\"n\">Thing</span><span class=\"p\">):</span>\n",
       "    <span class=\"sd\">&quot;&quot;&quot;An Agent is a subclass of Thing with one required instance attribute </span>\n",
       "<span class=\"sd\">    (aka slot), .program, which should hold a function that takes one argument,</span>\n",
       "<span class=\"sd\">    the percept, and returns an action. (What counts as a percept or action </span>\n",
       "<span class=\"sd\">    will depend on the specific environment in which the agent exists.)</span>\n",
       "<span class=\"sd\">    Note that &#39;program&#39; is a slot, not a method. If it were a method, then the</span>\n",
       "<span class=\"sd\">    program could &#39;cheat&#39; and look at aspects of the agent. It&#39;s not supposed</span>\n",
       "<span class=\"sd\">    to do that: the program can only look at the percepts. An agent program</span>\n",
       "<span class=\"sd\">    that needs a model of the world (and of the agent itself) will have to</span>\n",
       "<span class=\"sd\">    build and maintain its own model. There is an optional slot, .performance,</span>\n",
       "<span class=\"sd\">    which is a number giving the performance measure of the agent in its</span>\n",
       "<span class=\"sd\">    environment.&quot;&quot;&quot;</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"fm\">__init__</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">program</span><span class=\"o\">=</span><span class=\"kc\">None</span><span class=\"p\">):</span>\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">alive</span> <span class=\"o\">=</span> <span class=\"kc\">True</span>\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">bump</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">holding</span> <span class=\"o\">=</span> <span class=\"p\">[]</span>\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">=</span> <span class=\"mi\">0</span>\n",
       "        <span class=\"k\">if</span> <span class=\"n\">program</span> <span class=\"ow\">is</span> <span class=\"kc\">None</span> <span class=\"ow\">or</span> <span class=\"ow\">not</span> <span class=\"nb\">isinstance</span><span class=\"p\">(</span><span class=\"n\">program</span><span class=\"p\">,</span> <span class=\"n\">collections</span><span class=\"o\">.</span><span class=\"n\">abc</span><span class=\"o\">.</span><span class=\"n\">Callable</span><span class=\"p\">):</span>\n",
       "            <span class=\"nb\">print</span><span class=\"p\">(</span><span class=\"s2\">&quot;Can&#39;t find a valid program for </span><span class=\"si\">{}</span><span class=\"s2\">, falling back to default.&quot;</span><span class=\"o\">.</span><span class=\"n\">format</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"vm\">__class__</span><span class=\"o\">.</span><span class=\"vm\">__name__</span><span class=\"p\">))</span>\n",
       "\n",
       "            <span class=\"k\">def</span> <span class=\"nf\">program</span><span class=\"p\">(</span><span class=\"n\">percept</span><span class=\"p\">):</span>\n",
       "                <span class=\"k\">return</span> <span class=\"nb\">eval</span><span class=\"p\">(</span><span class=\"nb\">input</span><span class=\"p\">(</span><span class=\"s1\">&#39;Percept=</span><span class=\"si\">{}</span><span class=\"s1\">; action? &#39;</span><span class=\"o\">.</span><span class=\"n\">format</span><span class=\"p\">(</span><span class=\"n\">percept</span><span class=\"p\">)))</span>\n",
       "\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">program</span> <span class=\"o\">=</span> <span class=\"n\">program</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"nf\">can_grab</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">thing</span><span class=\"p\">):</span>\n",
       "        <span class=\"sd\">&quot;&quot;&quot;Return True if this agent can grab this thing.</span>\n",
       "<span class=\"sd\">        Override for appropriate subclasses of Agent and Thing.&quot;&quot;&quot;</span>\n",
       "        <span class=\"k\">return</span> <span class=\"kc\">False</span>\n",
       "</pre></div>\n",
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       "<h2></h2>\n",
       "\n",
       "<div class=\"highlight\"><pre><span></span><span class=\"k\">class</span> <span class=\"nc\">VacuumEnvironment</span><span class=\"p\">(</span><span class=\"n\">XYEnvironment</span><span class=\"p\">):</span>\n",
       "    <span class=\"sd\">&quot;&quot;&quot;The environment of [Ex. 2.12]. Agent perceives dirty or clean,</span>\n",
       "<span class=\"sd\">    and bump (into obstacle) or not; 2D discrete world of unknown size;</span>\n",
       "<span class=\"sd\">    performance measure is 100 for each dirt cleaned, and -1 for</span>\n",
       "<span class=\"sd\">    each turn taken.&quot;&quot;&quot;</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"fm\">__init__</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">width</span><span class=\"o\">=</span><span class=\"mi\">10</span><span class=\"p\">,</span> <span class=\"n\">height</span><span class=\"o\">=</span><span class=\"mi\">10</span><span class=\"p\">):</span>\n",
       "        <span class=\"nb\">super</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"fm\">__init__</span><span class=\"p\">(</span><span class=\"n\">width</span><span class=\"p\">,</span> <span class=\"n\">height</span><span class=\"p\">)</span>\n",
       "        <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">add_walls</span><span class=\"p\">()</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"nf\">thing_classes</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">):</span>\n",
       "        <span class=\"k\">return</span> <span class=\"p\">[</span><span class=\"n\">Wall</span><span class=\"p\">,</span> <span class=\"n\">Dirt</span><span class=\"p\">,</span> <span class=\"n\">ReflexVacuumAgent</span><span class=\"p\">,</span> <span class=\"n\">RandomVacuumAgent</span><span class=\"p\">,</span>\n",
       "                <span class=\"n\">TableDrivenVacuumAgent</span><span class=\"p\">,</span> <span class=\"n\">ModelBasedVacuumAgent</span><span class=\"p\">]</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"nf\">percept</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">agent</span><span class=\"p\">):</span>\n",
       "        <span class=\"sd\">&quot;&quot;&quot;The percept is a tuple of (&#39;Dirty&#39; or &#39;Clean&#39;, &#39;Bump&#39; or &#39;None&#39;).</span>\n",
       "<span class=\"sd\">        Unlike the TrivialVacuumEnvironment, location is NOT perceived.&quot;&quot;&quot;</span>\n",
       "        <span class=\"n\">status</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"s1\">&#39;Dirty&#39;</span> <span class=\"k\">if</span> <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">some_things_at</span><span class=\"p\">(</span>\n",
       "            <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">,</span> <span class=\"n\">Dirt</span><span class=\"p\">)</span> <span class=\"k\">else</span> <span class=\"s1\">&#39;Clean&#39;</span><span class=\"p\">)</span>\n",
       "        <span class=\"n\">bump</span> <span class=\"o\">=</span> <span class=\"p\">(</span><span class=\"s1\">&#39;Bump&#39;</span> <span class=\"k\">if</span> <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">bump</span> <span class=\"k\">else</span> <span class=\"s1\">&#39;None&#39;</span><span class=\"p\">)</span>\n",
       "        <span class=\"k\">return</span> <span class=\"n\">status</span><span class=\"p\">,</span> <span class=\"n\">bump</span>\n",
       "\n",
       "    <span class=\"k\">def</span> <span class=\"nf\">execute_action</span><span class=\"p\">(</span><span class=\"bp\">self</span><span class=\"p\">,</span> <span class=\"n\">agent</span><span class=\"p\">,</span> <span class=\"n\">action</span><span class=\"p\">):</span>\n",
       "        <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">bump</span> <span class=\"o\">=</span> <span class=\"kc\">False</span>\n",
       "        <span class=\"k\">if</span> <span class=\"n\">action</span> <span class=\"o\">==</span> <span class=\"s1\">&#39;Suck&#39;</span><span class=\"p\">:</span>\n",
       "            <span class=\"n\">dirt_list</span> <span class=\"o\">=</span> <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">list_things_at</span><span class=\"p\">(</span><span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">location</span><span class=\"p\">,</span> <span class=\"n\">Dirt</span><span class=\"p\">)</span>\n",
       "            <span class=\"k\">if</span> <span class=\"n\">dirt_list</span> <span class=\"o\">!=</span> <span class=\"p\">[]:</span>\n",
       "                <span class=\"n\">dirt</span> <span class=\"o\">=</span> <span class=\"n\">dirt_list</span><span class=\"p\">[</span><span class=\"mi\">0</span><span class=\"p\">]</span>\n",
       "                <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">+=</span> <span class=\"mi\">100</span>\n",
       "                <span class=\"bp\">self</span><span class=\"o\">.</span><span class=\"n\">delete_thing</span><span class=\"p\">(</span><span class=\"n\">dirt</span><span class=\"p\">)</span>\n",
       "        <span class=\"k\">else</span><span class=\"p\">:</span>\n",
       "            <span class=\"nb\">super</span><span class=\"p\">()</span><span class=\"o\">.</span><span class=\"n\">execute_action</span><span class=\"p\">(</span><span class=\"n\">agent</span><span class=\"p\">,</span> <span class=\"n\">action</span><span class=\"p\">)</span>\n",
       "\n",
       "        <span class=\"k\">if</span> <span class=\"n\">action</span> <span class=\"o\">!=</span> <span class=\"s1\">&#39;NoOp&#39;</span><span class=\"p\">:</span>\n",
       "            <span class=\"n\">agent</span><span class=\"o\">.</span><span class=\"n\">performance</span> <span class=\"o\">-=</span> <span class=\"mi\">1</span>\n",
       "</pre></div>\n",
       "</body>\n",
       "</html>\n"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from agents import *\n",
    "from notebook import psource\n",
    "psource(Agent)\n",
    "\n",
    "\n",
    "\n",
    "class XYEnvironments(Environment):\n",
    "    \"\"\"This class is for environments on a 2D plane, with locations\n",
    "    labelled by (x, y) points, either discrete or continuous.\n",
    "\n",
    "    Agents perceive things within a radius. Each agent in the\n",
    "    environment has a .location slot which should be a location such\n",
    "    as (0, 1), and a .holding slot, which should be a list of things\n",
    "    that are held.\"\"\"\n",
    "\n",
    "    def __init__(self, width=10, height=10):\n",
    "        super().__init__()\n",
    "\n",
    "        self.width = width\n",
    "        self.height = height\n",
    "        self.observers = []\n",
    "        # Sets iteration start and end (no walls).\n",
    "        self.x_start, self.y_start = (0, 0)\n",
    "        self.x_end, self.y_end = (self.width, self.height)\n",
    "\n",
    "    perceptible_distance = 1\n",
    "\n",
    "    def things_near(self, location, radius=None):\n",
    "        \"\"\"Return all things within radius of location.\"\"\"\n",
    "        if radius is None:\n",
    "            radius = self.perceptible_distance\n",
    "        radius2 = radius * radius\n",
    "        return [(thing, radius2 - distance_squared(location, thing.location))\n",
    "                for thing in self.things if distance_squared(\n",
    "                location, thing.location) <= radius2]\n",
    "\n",
    "    def percept(self, agent):\n",
    "        \"\"\"By default, agent perceives things within a default radius.\"\"\"\n",
    "        return self.things_near(agent.location)\n",
    "\n",
    "    def execute_action(self, agent, action):\n",
    "        agent.bump = False\n",
    "        if action == 'TurnRight':\n",
    "            print('{} decided to {} at location: {}'.format(str(agent)[1:-1], action, agent.location))\n",
    "            agent.direction += Direction.R\n",
    "        elif action == 'TurnLeft':\n",
    "            print('{} decided to {} at location: {}'.format(str(agent)[1:-1], action, agent.location))\n",
    "            agent.direction += Direction.L\n",
    "        elif action == 'Forward':\n",
    "            print('{} decided to move {}wards at location: {}'.format(str(agent)[1:-1], agent.direction.direction,\n",
    "                                                                      agent.location))\n",
    "            agent.bump = self.move_to(agent, agent.direction.move_forward(agent.location))\n",
    "        elif action == 'Grab':\n",
    "            things = [thing for thing in self.list_things_at(agent.location) if agent.can_grab(thing)]\n",
    "            if things:\n",
    "                agent.holding.append(things[0])\n",
    "                print(\"Grabbing \", things[0].__class__.__name__)\n",
    "                self.delete_thing(things[0])\n",
    "        elif action == 'Release':\n",
    "            if agent.holding:\n",
    "                dropped = agent.holding.pop()\n",
    "                print(\"Dropping \", dropped.__class__.__name__)\n",
    "                self.add_thing(dropped, location=agent.location)\n",
    "\n",
    "    def default_location(self, thing):\n",
    "        location = self.random_location_inbounds()\n",
    "        while self.some_things_at(location, Obstacle):\n",
    "            # we will find a random location with no obstacles\n",
    "            location = self.random_location_inbounds()\n",
    "        return location\n",
    "\n",
    "    def move_to(self, thing, destination):\n",
    "        \"\"\"Move a thing to a new location. Returns True on success or False if there is an Obstacle.\n",
    "        If thing is holding anything, they move with him.\"\"\"\n",
    "        thing.bump = self.some_things_at(destination, Obstacle)\n",
    "        if not thing.bump:\n",
    "            thing.location = destination\n",
    "            for o in self.observers:\n",
    "                o.thing_moved(thing)\n",
    "            for t in thing.holding:\n",
    "                self.delete_thing(t)\n",
    "                self.add_thing(t, destination)\n",
    "                t.location = destination\n",
    "        return thing.bump\n",
    "\n",
    "    def add_thing(self, thing, location=None, exclude_duplicate_class_items=False):\n",
    "        \"\"\"Add things to the world. If (exclude_duplicate_class_items) then the item won't be\n",
    "        added if the location has at least one item of the same class.\"\"\"\n",
    "        if location is None:\n",
    "            super().add_thing(thing)\n",
    "        elif self.is_inbounds(location):\n",
    "            if (exclude_duplicate_class_items and\n",
    "                    any(isinstance(t, thing.__class__) for t in self.list_things_at(location))):\n",
    "                return\n",
    "            super().add_thing(thing, location)\n",
    "\n",
    "    def is_inbounds(self, location):\n",
    "        \"\"\"Checks to make sure that the location is inbounds (within walls if we have walls)\"\"\"\n",
    "        x, y = location\n",
    "        return not (x < self.x_start or x > self.x_end or y < self.y_start or y > self.y_end)\n",
    "\n",
    "    def random_location_inbounds(self, exclude=None):\n",
    "        \"\"\"Returns a random location that is inbounds (within walls if we have walls)\"\"\"\n",
    "        location = (random.randint(self.x_start, self.x_end),\n",
    "                    random.randint(self.y_start, self.y_end))\n",
    "        if exclude is not None:\n",
    "            while location == exclude:\n",
    "                location = (random.randint(self.x_start, self.x_end),\n",
    "                            random.randint(self.y_start, self.y_end))\n",
    "        return location\n",
    "\n",
    "    def delete_thing(self, thing):\n",
    "        \"\"\"Deletes thing, and everything it is holding (if thing is an agent)\"\"\"\n",
    "        if isinstance(thing, Agent):\n",
    "            del thing.holding\n",
    "\n",
    "        super().delete_thing(thing)\n",
    "        for obs in self.observers:\n",
    "            obs.thing_deleted(thing)\n",
    "\n",
    "    def add_walls(self):\n",
    "        \"\"\"Put walls around the entire perimeter of the grid.\"\"\"\n",
    "        for x in range(self.width):\n",
    "            self.add_thing(Wall(), (x, 0))\n",
    "            self.add_thing(Wall(), (x, self.height - 1))\n",
    "        for y in range(1, self.height - 1):\n",
    "            self.add_thing(Wall(), (0, y))\n",
    "            self.add_thing(Wall(), (self.width - 1, y))\n",
    "\n",
    "        # Updates iteration start and end (with walls).\n",
    "        self.x_start, self.y_start = (1, 1)\n",
    "        self.x_end, self.y_end = (self.width - 1, self.height - 1)\n",
    "\n",
    "    def add_observer(self, observer):\n",
    "        \"\"\"Adds an observer to the list of observers.\n",
    "        An observer is typically an EnvGUI.\n",
    "\n",
    "        Each observer is notified of changes in move_to and add_thing,\n",
    "        by calling the observer's methods thing_moved(thing)\n",
    "        and thing_added(thing, loc).\"\"\"\n",
    "        self.observers.append(observer)\n",
    "\n",
    "    def turn_heading(self, heading, inc):\n",
    "        \"\"\"Return the heading to the left (inc=+1) or right (inc=-1) of heading.\"\"\"\n",
    "        return turn_heading(heading, inc)\n",
    "\n",
    "\n",
    "\n",
    "class VacuumEnvironments(XYEnvironments):\n",
    "    \"\"\"The environment of [Ex. 2.12]. Agent perceives dirty or clean,\n",
    "    and bump (into obstacle) or not; 2D discrete world of unknown size;\n",
    "    performance measure is 100 for each dirt cleaned, and -1 for\n",
    "    each turn taken.\"\"\"\n",
    "\n",
    "    def __init__(self, width=10, height=10):\n",
    "        super().__init__(width, height)\n",
    "        self.add_walls()\n",
    "\n",
    "    def thing_classes(self):\n",
    "        return [Wall, Dirt, ReflexVacuumAgent, RandomVacuumAgent,\n",
    "                TableDrivenVacuumAgent, ModelBasedVacuumAgent]\n",
    "\n",
    "    def percept(self, agent):\n",
    "        \"\"\"The percept is a tuple of ('Dirty' or 'Clean', 'Bump' or 'None').\n",
    "        Unlike the TrivialVacuumEnvironment, location is NOT perceived.\"\"\"\n",
    "        status = ('Dirty' if self.some_things_at(\n",
    "            agent.location, Dirt) else 'Clean')\n",
    "        bump = ('Bump' if agent.bump else 'None')\n",
    "        return status, bump\n",
    "\n",
    "    def execute_action(self, agent, action):\n",
    "        agent.bump = False\n",
    "        if action == 'Suck':\n",
    "            dirt_list = self.list_things_at(agent.location, Dirt)\n",
    "            if dirt_list != []:\n",
    "                print('{} suck {} at location: {}'\n",
    "                      .format(str(agent)[1:-1], str(items[0])[1:-1], agent.location))\n",
    "                dirt = dirt_list[0]\n",
    "                agent.performance += 100\n",
    "                self.delete_thing(dirt)\n",
    "        else:\n",
    "            super().execute_action(agent, action)\n",
    "\n",
    "        if action != 'NoOp':\n",
    "            agent.performance -= 1\n",
    "\n",
    "\n",
    "psource(VacuumEnvironment)\n",
    "Env_2D = VacuumEnvironment(3,3)\n",
    "Programm = RandomAgentProgram(['TurnRight', 'TurnLeft', 'Forward' , 'Suck', 'NoOp'])\n",
    "Random_Vacuum_Agent = Agent(program=Programm)\n",
    "Env_2D.add_thing(Random_Vacuum_Agent,[0,0])\n",
    "dirt = Dirt()\n",
    "dirt2 = Dirt()\n",
    "Env_2D.add_thing(dirt,[1,1])\n",
    "Env_2D.add_thing(dirt2,[2,2])\n",
    "TraceAgent(Random_Vacuum_Agent)\n",
    "Env_2D.run(10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3885cdfb",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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