@@ -462,7 +462,7 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "def f(x, offset):\n",

+    "def f(x, offset=0):\n",

     "    a = 0.01\n",

     "    return x + a**2 / (a**2 + (x - offset)**2)\n",

     "\n",

@@ -470,7 +470,8 @@

     "            bounds=(-1, 1)) for i in range(10)]\n",

     "\n",

     "bal_learner = adaptive.BalancingLearner(learners)\n",

-    "runner = adaptive.Runner(bal_learner, goal=lambda l: l.loss() < 0.01)"

+    "runner = adaptive.Runner(bal_learner, goal=lambda l: l.loss() < 0.01)\n",

+    "runner.live_info()"

    ]

   },

   {

@@ -618,7 +619,8 @@

     "executor = ProcessPoolExecutor(max_workers=4)\n",

     "\n",

     "learner = adaptive.Learner1D(f, bounds=(-1, 1))\n",

-    "runner = adaptive.Runner(learner, executor=executor, goal=lambda l: l.loss() < 0.1)\n",

+    "runner = adaptive.Runner(learner, executor=executor, goal=lambda l: l.loss() < 0.05)\n",

+    "runner.live_info()\n",

     "runner.live_plot()"

    ]

   },

@@ -642,7 +644,8 @@

     "client[:].use_cloudpickle()\n",

     "\n",

     "learner = adaptive.Learner1D(f, bounds=(-1, 1))\n",

-    "runner = adaptive.Runner(learner, executor=client, goal=lambda l: l.loss() < 0.1)\n",

+    "runner = adaptive.Runner(learner, executor=client, goal=lambda l: l.loss() < 0.01)\n",

+    "runner.live_info()\n",

     "runner.live_plot()"

    ]

   },

@@ -693,7 +696,16 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "runner.task.cancel()"

+    "runner.cancel()"

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "metadata": {},

+   "outputs": [],

+   "source": [

+    "print(runner.status())"

    ]

   },

   {

@@ -789,7 +801,7 @@

     "learner = adaptive.Learner1D(f, bounds=(-1, 1))\n",

     "runner = adaptive.Runner(learner, goal=lambda l: l.loss() < 0.1,\n",

     "                         log=True)\n",

-    "runner.live_plot()"

+    "runner.live_info()"

    ]

   },

   {