{
"cells": [
{
"cell_type": "markdown",
"id": "2546904a",
"metadata": {},
"source": [
"# Gymnasium integration\n",
"[Gymnasium](https://gymnasium.farama.org/) is an API standard for reinforcement learning with a diverse collection of reference environments. Stormvogel supports some integration with gymnasium. In particular, you can construct explicit models from the gymnasium environmnents under Gymnasium's [ToyText](https://gymnasium.farama.org/environments/toy_text/) (except Blackjack)."
]
},
{
"cell_type": "markdown",
"id": "80d60d9b",
"metadata": {},
"source": [
"## FrozenLake\n",
"Let us create one of these environments, called FrozenLake.\n",
"Our agent wants to get to the present. Currently, it just chooses a random action."
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "9aa5d75e",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:14.557703Z",
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"shell.execute_reply": "2026-04-16T05:27:14.994774Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"![](\"gifs/ice1.gif\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"import gymnasium as gym\n",
"from stormvogel.extensions.gym_grid import *\n",
"from stormvogel import *\n",
"\n",
"env = gym.make(\n",
" \"FrozenLake-v1\", render_mode=\"rgb_array\", is_slippery=False\n",
") # Set `is_slippery=True` for stochastic behavior\n",
"filename = gymnasium_render_model_gif(env, filename=\"ice1\")\n",
"extensions.embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "8efd9528",
"metadata": {},
"source": [
"We can convert it into an explicit MDP as follows. Each state has a label that relates to the coordinates of the tile."
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "9fc0361b",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:14.997436Z",
"iopub.status.busy": "2026-04-16T05:27:14.997166Z",
"iopub.status.idle": "2026-04-16T05:27:15.190202Z",
"shell.execute_reply": "2026-04-16T05:27:15.189639Z"
}
},
"outputs": [
{
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"\n",
"\n",
"\n",
" \n",
" Network\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n"
],
"text/plain": [
""
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},
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""
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},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sv_model = gymnasium_grid_to_stormvogel(env, GRID_ACTION_LABEL_MAP)\n",
"# GRID_ACTION_LABEL_MAP = {0: \"←\", 1: \"↓\", 2: \"→\", 3: \"↑\", 4: \"pickup\", 5: \"dropoff\"} (map between gymnasium action ids and labels)\n",
"show(sv_model)"
]
},
{
"cell_type": "markdown",
"id": "aad967ec",
"metadata": {},
"source": [
"Now, let's do some model checking to calculate a strategy to solve the puzzle. We will tell the model checker to maximize the probability of getting to the target state (the present)."
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "23e6b42e",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:15.197857Z",
"iopub.status.busy": "2026-04-16T05:27:15.197505Z",
"iopub.status.idle": "2026-04-16T05:27:15.235973Z",
"shell.execute_reply": "2026-04-16T05:27:15.235133Z"
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"outputs": [
{
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"\n",
"\n",
"\n",
" \n",
" Network\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"res = model_checking(sv_model, 'Pmax=? [F \"target\"]')\n",
"vis2 = show(sv_model, result=res)"
]
},
{
"cell_type": "markdown",
"id": "aaa8ba6e",
"metadata": {},
"source": [
"Let's highlight the path to see what the scheduler is doing."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "868b4caf",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:15.243815Z",
"iopub.status.busy": "2026-04-16T05:27:15.243597Z",
"iopub.status.idle": "2026-04-16T05:27:30.304018Z",
"shell.execute_reply": "2026-04-16T05:27:30.303379Z"
}
},
"outputs": [],
"source": [
"path = simulate_path(sv_model, scheduler=res.scheduler, steps=20)\n",
"vis2.highlight_path(path, color=\"orange\")"
]
},
{
"cell_type": "markdown",
"id": "0ebf4628",
"metadata": {},
"source": [
"Alternatively, we can show what our scheduler does in the frozen lake environment itself."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "80c5cf3c",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.306034Z",
"iopub.status.busy": "2026-04-16T05:27:30.305850Z",
"iopub.status.idle": "2026-04-16T05:27:30.351967Z",
"shell.execute_reply": "2026-04-16T05:27:30.351342Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"![](\"gifs/ice2.gif\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from stormvogel.extensions.gym_grid import *\n",
"\n",
"gs = to_gymnasium_scheduler(sv_model, res.scheduler, GRID_ACTION_LABEL_MAP)\n",
"filename = gymnasium_render_model_gif(env, gs, filename=\"ice2\")\n",
"extensions.embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "91f58e3b",
"metadata": {},
"source": [
"We can also define a function to act as the scheduler on the model and convert it to a gymnasium scheduler. This one just keeps going in a loop..."
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "0710f5bf",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.353846Z",
"iopub.status.busy": "2026-04-16T05:27:30.353667Z",
"iopub.status.idle": "2026-04-16T05:27:30.653129Z",
"shell.execute_reply": "2026-04-16T05:27:30.652483Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"![](\"gifs/ice3.gif\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from stormvogel.model import Action\n",
"\n",
"\n",
"def my_scheduler(s: stormvogel.model.State):\n",
" # \"←\" \"↓\" \"→\" \"↑\"\n",
" if s.is_initial():\n",
" return Action(\"→\")\n",
" env_id = s.get_valuation(stormvogel.model.Variable(\"env_id\"))\n",
" x, y = to_coordinate(env_id, env)\n",
" if x < 2 and y == 0:\n",
" return Action(\"→\")\n",
" elif x == 2 and y < 2:\n",
" return Action(\"↓\")\n",
" elif x > 0 and y == 2:\n",
" return Action(\"←\")\n",
" else:\n",
" return Action(\"↑\")\n",
"\n",
"\n",
"gs = to_gymnasium_scheduler(sv_model, my_scheduler, GRID_ACTION_LABEL_MAP)\n",
"filename = gymnasium_render_model_gif(env, gs, filename=\"ice3\")\n",
"extensions.embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "cadeb305",
"metadata": {},
"source": [
"## CliffWalking\n",
"CliffWalking is a slightly more boring version of FrozenLake. You can apply the same principles that we just applied to FrozenLake."
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "bae11294",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.655283Z",
"iopub.status.busy": "2026-04-16T05:27:30.655087Z",
"iopub.status.idle": "2026-04-16T05:27:30.661983Z",
"shell.execute_reply": "2026-04-16T05:27:30.661360Z"
}
},
"outputs": [],
"source": [
"import gymnasium as gym\n",
"from stormvogel.extensions.gym_grid import *\n",
"\n",
"env = gym.make(\"CliffWalking-v1\", render_mode=\"rgb_array\")"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "82a1a462",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.663760Z",
"iopub.status.busy": "2026-04-16T05:27:30.663576Z",
"iopub.status.idle": "2026-04-16T05:27:30.703044Z",
"shell.execute_reply": "2026-04-16T05:27:30.702503Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
" \n",
" Network\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n"
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"text/plain": [
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"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"sv_model = gymnasium_grid_to_stormvogel(env, GRID_ACTION_LABEL_MAP)\n",
"show(sv_model)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "6b3eab59",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.710412Z",
"iopub.status.busy": "2026-04-16T05:27:30.710204Z",
"iopub.status.idle": "2026-04-16T05:27:30.903065Z",
"shell.execute_reply": "2026-04-16T05:27:30.902408Z"
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"outputs": [
{
"data": {
"text/html": [
"![](\"gifs/cliff.gif\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from stormvogel.stormpy_utils.model_checking import model_checking\n",
"\n",
"res = model_checking(sv_model, 'Pmax=? [F \"target\"]')\n",
"gs = to_gymnasium_scheduler(sv_model, res.scheduler, GRID_ACTION_LABEL_MAP)\n",
"filename = gymnasium_render_model_gif(env, gs, filename=\"cliff\")\n",
"extensions.embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "d33d7ea5",
"metadata": {},
"source": [
"## Taxi\n",
"In the Taxi scenario, a taxi has to pick up passengers and transport them to the hotel. The position of the target, passenger and taxi are chosen at random."
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "048b65ba",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:30.904966Z",
"iopub.status.busy": "2026-04-16T05:27:30.904767Z",
"iopub.status.idle": "2026-04-16T05:27:31.115190Z",
"shell.execute_reply": "2026-04-16T05:27:31.114542Z"
}
},
"outputs": [
{
"data": {
"text/plain": [
"'ModelType.MDP model with 3529 states, 6049 choices, and 1005 distinct labels.'"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import gymnasium as gym\n",
"from stormvogel.extensions.gym_grid import *\n",
"\n",
"env = gym.make(\n",
" \"Taxi-v3\", render_mode=\"rgb_array\"\n",
") # Set `is_slippery=True` for stochastic behavior\n",
"sv_model = gymnasium_grid_to_stormvogel(env)\n",
"# This model is so big that it is better not to display it.\n",
"sv_model.summary()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"id": "5de9fb9d",
"metadata": {
"execution": {
"iopub.execute_input": "2026-04-16T05:27:31.117021Z",
"iopub.status.busy": "2026-04-16T05:27:31.116830Z",
"iopub.status.idle": "2026-04-16T05:27:32.001873Z",
"shell.execute_reply": "2026-04-16T05:27:32.001285Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"![](\"gifs/taxi.gif\")
"
],
"text/plain": [
""
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"target = get_target_state(env)\n",
"res = model_checking(sv_model, \"Rmax=? [S]\")\n",
"gs = to_gymnasium_scheduler(sv_model, res.scheduler, GRID_ACTION_LABEL_MAP)\n",
"filename = gymnasium_render_model_gif(env, gs, filename=\"taxi\")\n",
"extensions.embed_gif(filename)"
]
}
],
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