diff --git a/docs/examples/tutorials/custom_optimization_loop.ipynb b/docs/examples/tutorials/custom_optimization_loop.ipynb
index 51b1ae6e..413c4d53 100644
--- a/docs/examples/tutorials/custom_optimization_loop.ipynb
+++ b/docs/examples/tutorials/custom_optimization_loop.ipynb
@@ -111,13 +111,13 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Iteration: 1 | my_swarm.best_cost: 0.0009\n",
+      "Iteration: 1 | my_swarm.best_cost: 0.0070\n",
       "Iteration: 21 | my_swarm.best_cost: 0.0000\n",
       "Iteration: 41 | my_swarm.best_cost: 0.0000\n",
       "Iteration: 61 | my_swarm.best_cost: 0.0000\n",
       "Iteration: 81 | my_swarm.best_cost: 0.0000\n",
       "The best cost found by our swarm is: 0.0000\n",
-      "The best position found by our swarm is: [3.30572365e-19 2.93696483e-19]\n"
+      "The best position found by our swarm is: [1.77943664e-18 2.49653561e-18]\n"
      ]
     }
    ],
@@ -126,7 +126,6 @@
     "for i in range(iterations):\n",
     "    # Part 1: Update personal best\n",
     "    my_swarm.current_cost = f(my_swarm.position) # Compute current cost\n",
-    "    my_swarm.pbest_cost = f(my_swarm.pbest_pos)  # Compute personal best pos\n",
     "    my_swarm.pbest_pos, my_swarm.pbest_cost = P.compute_pbest(my_swarm) # Update and store\n",
     "    \n",
     "    # Part 2: Update global best\n",
@@ -163,15 +162,15 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2019-05-18 15:39:20,737 - pyswarms.single.global_best - INFO - Optimize for 100 iters with {'c1': 0.6, 'c2': 0.3, 'w': 0.4}\n",
-      "pyswarms.single.global_best: 100%|██████████|100/100, best_cost=0.00418\n",
-      "2019-05-18 15:39:21,942 - pyswarms.single.global_best - INFO - Optimization finished | best cost: 0.004177699645933291, best pos: [0.03663518 0.05325001]\n"
+      "2023-10-20 14:44:14,240 - pyswarms.single.global_best - INFO - Optimize for 100 iters with {'c1': 0.6, 'c2': 0.3, 'w': 0.4}\n",
+      "pyswarms.single.global_best: 100%|██████████|100/100, best_cost=0.00596\n",
+      "2023-10-20 14:44:14,358 - pyswarms.single.global_best - INFO - Optimization finished | best cost: 0.0059581279236955356, best pos: [0.04219012 0.06463839]\n"
      ]
     },
     {
      "data": {
       "text/plain": [
-       "(0.004177699645933291, array([0.03663518, 0.05325001]))"
+       "(0.0059581279236955356, array([0.04219012, 0.06463839]))"
       ]
      },
      "execution_count": 4,
diff --git a/pyswarms/backend/swarms.py b/pyswarms/backend/swarms.py
index f3817cb3..e41a34d2 100644
--- a/pyswarms/backend/swarms.py
+++ b/pyswarms/backend/swarms.py
@@ -96,7 +96,6 @@ class Swarm(object):
     )
     pbest_cost = attrib(
         type=np.ndarray,
-        default=np.array([]),
         validator=instance_of(np.ndarray),
     )
     best_cost = attrib(
@@ -119,3 +118,7 @@ def dimensions_default(self):
     @pbest_pos.default
     def pbest_pos_default(self):
         return self.position
+    
+    @pbest_cost.default
+    def pbest_cost_default(self):
+        return np.full(shape=(self.position.shape[0],), fill_value=np.inf)