Updating getting-started notebook.

notebooks/getting-started.ipynb

    "source": [
     "### 1. Set environment parameters\n",
     "\n",
-    "Be sure to set `env_name` to the name of the Unity environment file you want to launch. Ensure that the environment build is in the `python/` directory."
+    "Be sure to set `env_name` to the name of the Unity environment file you want to launch. Ensure that the environment build is in the ML-Agents SDK directory."
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "env_name = \"../envs/3DBall\"  # Name of the Unity environment binary to launch\n",
     "    done = False\n",
     "    episode_rewards = 0\n",
     "    while not done:\n",
+    "        action_size = brain.vector_action_space_size\n",
-    "                                                brain.vector_action_space_size))[default_brain]\n",
+    "                                                action_size[0]))[default_brain]\n",
-    "            env_info = env.step(np.random.randint(0, brain.vector_action_space_size, \n",
-    "                                                  size=(len(env_info.agents))))[default_brain]\n",
+    "            action = np.column_stack([np.random.randint(0, action_size[i], size=(len(env_info.agents))) for i in range(len(action_size))])\n",
+    "            env_info = env.step(action)[default_brain]\n",
     "        episode_rewards += env_info.rewards[0]\n",
     "        done = env_info.local_done[0]\n",
     "    print(\"Total reward this episode: {}\".format(episode_rewards))"
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {
-    "collapsed": true
-   },
+   "metadata": {},
    "outputs": [],
    "source": [
     "env.close()"
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.6.2"
+   "version": "3.6.6"
   }
  },
  "nbformat": 4,