diff --git a/.python-version b/.python-version
index 2c07333..24ee5b1 100644
--- a/.python-version
+++ b/.python-version
@@ -1 +1 @@
-3.11
+3.13
diff --git a/M2/Reinforcement Learning/Lab 2 - Maze Game as a Markov Decision Process Part 1.ipynb b/M2/Reinforcement Learning/Lab 2 - Maze Game as a Markov Decision Process Part 1.ipynb
index ad74353..cc0c383 100644
--- a/M2/Reinforcement Learning/Lab 2 - Maze Game as a Markov Decision Process Part 1.ipynb	
+++ b/M2/Reinforcement Learning/Lab 2 - Maze Game as a Markov Decision Process Part 1.ipynb	
@@ -31,7 +31,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 73,
+   "execution_count": null,
    "id": "100d1e0d",
    "metadata": {},
    "outputs": [],
@@ -42,7 +42,9 @@
     "np.set_printoptions(\n",
     "    precision=3,\n",
     "    suppress=True,\n",
-    ")  # (not mandatory) This line is for limiting floats to 3 decimal places, avoiding scientific notation (like 1.23e-04) for small numbers.\n",
+    ")\n",
+    "# (not mandatory) This line is for limiting floats to 3 decimal places,\n",
+    "# avoiding scientific notation (like 1.23e-04) for small numbers.\n",
     "\n",
     "# For reproducibility\n",
     "rng = np.random.default_rng(seed=42)  # This line creates a random number generator."
@@ -229,7 +231,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 78,
+   "execution_count": null,
    "id": "a1258de4",
    "metadata": {},
    "outputs": [
@@ -249,18 +251,17 @@
     "pos_to_state = {}  # (i,j) -> s\n",
     "\n",
     "start_state = None  # will store the state index of start state\n",
-    "goal_states = []  # will store the state index of goal state # We use a list in case there are multiple goals\n",
-    "trap_states = []  # will store the state index of trap state # We use a list in case there are multiple traps\n",
+    "goal_states = []  # will store the state index of goal state\n",
+    "trap_states = []  # will store the state index of trap state\n",
     "\n",
     "s = 0\n",
     "for i in range(n_rows):  # i = row index\n",
     "    for j in range(n_cols):  # j = column index\n",
     "        cell = maze_str[i][j]  # cell = the character at that position (S, ., #, etc.)\n",
     "\n",
-    "        if (\n",
-    "            cell in FREE\n",
-    "        ):  # FREE contains: free cells \".\", start cell \"S\", goal cell \"G\" and trap cell \"X\"\n",
-    "            # Walls # are ignored, they are not MDP states.\n",
+    "        if cell in FREE:\n",
+    "        # FREE contains: free cells \".\", start cell \"S\", goal cell \"G\" and trap cell \"X\"\n",
+    "        # Walls # are ignored, they are not MDP states.\n",
     "            state_to_pos[s] = (i, j)\n",
     "            pos_to_state[(i, j)] = s\n",
     "\n",
@@ -365,7 +366,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 80,
+   "execution_count": null,
    "id": "fc61ceef-217c-47f4-8eba-0353369210db",
    "metadata": {},
    "outputs": [
@@ -398,7 +399,7 @@
     "    for (\n",
     "        s,\n",
     "        (i, j),\n",
-    "    ) in state_to_pos.items():  # Calling .items() returns a list-like sequence of (key, value) pairs in the dictionary.\n",
+    "    ) in state_to_pos.items():\n",
     "        cell = maze_str[i][j]\n",
     "\n",
     "        if cell == \"S\":\n",
@@ -517,7 +518,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 83,
+   "execution_count": null,
    "id": "4b06da5e-bc63-48e5-a336-37bce952443d",
    "metadata": {},
    "outputs": [],
@@ -967,7 +968,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 91,
+   "execution_count": null,
    "id": "2fffe0b7",
    "metadata": {},
    "outputs": [],
@@ -1109,7 +1110,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 94,
+   "execution_count": null,
    "id": "4c428327",
    "metadata": {},
    "outputs": [
@@ -1125,7 +1126,7 @@
     }
    ],
    "source": [
-    "def plot_values(V: np.ndarray, title=\"Value function\") -> None:\n",
+    "def plot_values(V: np.ndarray, title: str = \"Value function\") -> None:\n",
     "    \"\"\"Plot the value function V on the maze as a heatmap.\"\"\"\n",
     "    grid_values = np.full(\n",
     "        (n_rows, n_cols),\n",
@@ -1149,7 +1150,7 @@
     "    # For each state:\n",
     "    # Place the text label at (column j, row i).\n",
     "    # Display value to two decimals.\n",
-    "    # Use white text so it’s visible on the heatmap.\n",
+    "    # Use white text so it's visible on the heatmap.\n",
     "    # Center the text inside each cell.\n",
     "\n",
     "    for s, (i, j) in state_to_pos.items():\n",
@@ -1183,12 +1184,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 95,
+   "execution_count": null,
    "id": "c1ab67f0-bd5e-4ffe-b655-aec030401b78",
    "metadata": {},
    "outputs": [],
    "source": [
-    "def plot_policy(policy: np.ndarray, title=\"Policy\") -> None:\n",
+    "def plot_policy(policy: np.ndarray, title: str =\"Policy\") -> None:\n",
     "    \"\"\"Plot the given policy on the maze.\"\"\"\n",
     "    _fig, ax = plt.subplots()\n",
     "    # draw walls as dark cells\n",
@@ -1253,7 +1254,7 @@
     "    ax.set_yticks(np.arange(-0.5, n_rows, 1))\n",
     "    ax.set_xticklabels([])\n",
     "    ax.set_yticklabels([])\n",
-    "    ax.grid(True)\n",
+    "    ax.grid(visible=True)\n",
     "    ax.set_title(title)\n",
     "    plt.show()"
    ]
@@ -1297,7 +1298,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 97,
+   "execution_count": null,
    "id": "929707e6-3022-4d86-96cc-12f251f890a9",
    "metadata": {},
    "outputs": [
@@ -1323,35 +1324,37 @@
     }
    ],
    "source": [
-    "my_policy = [\n",
-    "    A_RIGHT,\n",
-    "    A_RIGHT,\n",
-    "    A_RIGHT,\n",
-    "    A_DOWN,\n",
-    "    A_DOWN,  # First row\n",
-    "    A_UP,\n",
-    "    A_DOWN,\n",
-    "    A_DOWN,\n",
-    "    A_LEFT,  # Second row\n",
-    "    A_UP,\n",
-    "    A_RIGHT,\n",
-    "    A_DOWN,  # Third row\n",
-    "    A_UP,\n",
-    "    A_LEFT,\n",
-    "    A_RIGHT,\n",
-    "    A_RIGHT,\n",
-    "    A_RIGHT,  # Fourth row\n",
-    "    A_UP,\n",
-    "    A_LEFT,\n",
-    "    A_DOWN,\n",
-    "    A_RIGHT,\n",
-    "    A_UP,  # Fifth row\n",
-    "]\n",
+    "my_policy = np.ndarray(\n",
+    "    [\n",
+    "        A_RIGHT,\n",
+    "        A_RIGHT,\n",
+    "        A_RIGHT,\n",
+    "        A_DOWN,\n",
+    "        A_DOWN,  # First row\n",
+    "        A_UP,\n",
+    "        A_DOWN,\n",
+    "        A_DOWN,\n",
+    "        A_LEFT,  # Second row\n",
+    "        A_UP,\n",
+    "        A_RIGHT,\n",
+    "        A_DOWN,  # Third row\n",
+    "        A_UP,\n",
+    "        A_LEFT,\n",
+    "        A_RIGHT,\n",
+    "        A_RIGHT,\n",
+    "        A_RIGHT,  # Fourth row\n",
+    "        A_UP,\n",
+    "        A_LEFT,\n",
+    "        A_DOWN,\n",
+    "        A_RIGHT,\n",
+    "        A_UP,  # Fifth row\n",
+    "    ],\n",
+    ")\n",
     "\n",
     "V_my_policy = policy_evaluation(policy=my_policy, P=P, R=R, gamma=gamma)\n",
     "\n",
     "plot_values(V=V_my_policy, title=\"Value function: my policy\")\n",
-    "plot_policy(policy=my_policy, title=\"My policy\")"
+    "plot_policy(policy=my_policy, title=\"My policy\")\n"
    ]
   },
   {
@@ -1400,7 +1403,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.13.9"
+   "version": "3.11.12"
   }
  },
  "nbformat": 4,
diff --git a/pyproject.toml b/pyproject.toml
index 52c3249..4eb4a16 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -51,7 +51,7 @@ select = ["ALL"]
 
 # Désactiver certaines règles
 ignore = [
-    # "E501", # line too long, géré par le formatter
+    "E501", # line too long, géré par le formatter
     "E402", # Imports in top of file
     "T201", # Print
     "N806",