{
"cells": [
{
"cell_type": "markdown",
"id": "2fd419a9",
"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": "3c2d4d13",
"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": "449b20a9",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:23.313105Z",
"iopub.status.busy": "2026-10-01T12:39:23.312813Z",
"iopub.status.idle": "2026-10-01T12:39:24.040555Z",
"shell.execute_reply": "2026-10-01T12:39:24.040012Z"
}
},
"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.extensions.gifs import embed_gif\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",
"embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "d7145507",
"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": "00ae1fed",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:24.042494Z",
"iopub.status.busy": "2026-10-01T12:39:24.042259Z",
"iopub.status.idle": "2026-10-01T12:39:24.234555Z",
"shell.execute_reply": "2026-10-01T12:39:24.234023Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
" \n",
" Network\n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
" \n",
"\n"
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"text/plain": [
""
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},
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"data": {
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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": "14b17afe",
"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": "6919c0db",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:24.256120Z",
"iopub.status.busy": "2026-10-01T12:39:24.255805Z",
"iopub.status.idle": "2026-10-01T12:39:24.287125Z",
"shell.execute_reply": "2026-10-01T12:39:24.286533Z"
}
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"outputs": [
{
"data": {
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"\n",
"\n",
"\n",
" \n",
" Network\n",
" \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": "e1a99f10",
"metadata": {},
"source": [
"Let's highlight the path to see what the scheduler is doing."
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "716188a8",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:24.305518Z",
"iopub.status.busy": "2026-10-01T12:39:24.305271Z",
"iopub.status.idle": "2026-10-01T12:39:39.359322Z",
"shell.execute_reply": "2026-10-01T12:39:39.358804Z"
}
},
"outputs": [],
"source": [
"path = simulate_path(sv_model, scheduler=res.scheduler, steps=20)\n",
"vis2.highlight_path(path, color=\"orange\")"
]
},
{
"cell_type": "markdown",
"id": "7f1804f4",
"metadata": {},
"source": [
"Alternatively, we can show what our scheduler does in the frozen lake environment itself."
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "a40f12dc",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.361193Z",
"iopub.status.busy": "2026-10-01T12:39:39.361005Z",
"iopub.status.idle": "2026-10-01T12:39:39.407471Z",
"shell.execute_reply": "2026-10-01T12:39:39.406869Z"
}
},
"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",
"embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "ea01920e",
"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": "a4c286d5",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.409460Z",
"iopub.status.busy": "2026-10-01T12:39:39.409269Z",
"iopub.status.idle": "2026-10-01T12:39:39.713124Z",
"shell.execute_reply": "2026-10-01T12:39:39.712485Z"
}
},
"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",
"embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "1c14dca9",
"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": "66b8036e",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.715144Z",
"iopub.status.busy": "2026-10-01T12:39:39.714954Z",
"iopub.status.idle": "2026-10-01T12:39:39.720968Z",
"shell.execute_reply": "2026-10-01T12:39:39.720359Z"
}
},
"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": "fb58a569",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.722692Z",
"iopub.status.busy": "2026-10-01T12:39:39.722525Z",
"iopub.status.idle": "2026-10-01T12:39:39.758574Z",
"shell.execute_reply": "2026-10-01T12:39:39.757931Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"\n",
"\n",
"\n",
" \n",
" Network\n",
" \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": "3bf1f1ae",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.778224Z",
"iopub.status.busy": "2026-10-01T12:39:39.777980Z",
"iopub.status.idle": "2026-10-01T12:39:39.968377Z",
"shell.execute_reply": "2026-10-01T12:39:39.967867Z"
}
},
"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",
"embed_gif(filename)"
]
},
{
"cell_type": "markdown",
"id": "9c2981af",
"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": "dcb906c8",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:39.970204Z",
"iopub.status.busy": "2026-10-01T12:39:39.970032Z",
"iopub.status.idle": "2026-10-01T12:39:40.183509Z",
"shell.execute_reply": "2026-10-01T12:39:40.183017Z"
}
},
"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-v4\", 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": "7df0ea8f",
"metadata": {
"execution": {
"iopub.execute_input": "2026-10-01T12:39:40.185235Z",
"iopub.status.busy": "2026-10-01T12:39:40.185068Z",
"iopub.status.idle": "2026-10-01T12:39:41.111446Z",
"shell.execute_reply": "2026-10-01T12:39:41.110790Z"
}
},
"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",
"embed_gif(filename)"
]
}
],
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