# rlenvironments
`rlenvironments` is a Python library that provides an environment called `TargetSeeker` for reinforcement learning tasks involving target seeking. It allows agents to navigate towards a target point in a bounded environment.
## Installation
pip install rlenvironments
## Usage
To use the `TargetSeeker` environment, you can follow this example:
```python
from rlenvironments.target_seeker import TargetSeeker
# Create an instance of TargetSeeker environment
env = TargetSeeker(image_option='show', output_interval=5)
for _ in range(20):
# Reset the environment
state = env.reset()
while not env.episode_ended:
# Choose an action
action = env.random_action()
# Take a step in the environment
next_state, reward, done = env.step(action)
# Do something with the results
[Output 1](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output1.png)
[Output 2](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output2.png)
[Output 3](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output3.png)
[Output 4](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output4.png)
Raw data
{
"_id": null,
"home_page": "https://github.com/ukoksoy/rlenvironments",
"name": "rlenvironments",
"maintainer": "",
"docs_url": null,
"requires_python": ">=3.7",
"maintainer_email": "",
"keywords": "reinforcement-learning environment target-seeking",
"author": "Umut Koksoy",
"author_email": "umutkoksoy@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/58/39/288e86308206735505ab444b7554b3755165fc167921da090214c2a6a7be/rlenvironments-0.2.2.tar.gz",
"platform": null,
"description": "# rlenvironments\r\n\r\n`rlenvironments` is a Python library that provides an environment called `TargetSeeker` for reinforcement learning tasks involving target seeking. It allows agents to navigate towards a target point in a bounded environment.\r\n\r\n## Installation\r\n\r\npip install rlenvironments\r\n\r\n\r\n## Usage\r\n\r\nTo use the `TargetSeeker` environment, you can follow this example:\r\n\r\n```python\r\nfrom rlenvironments.target_seeker import TargetSeeker\r\n\r\n# Create an instance of TargetSeeker environment\r\nenv = TargetSeeker(image_option='show', output_interval=5)\r\n\r\nfor _ in range(20):\r\n\r\n # Reset the environment\r\n state = env.reset()\r\n\r\n while not env.episode_ended:\r\n\r\n # Choose an action\r\n action = env.random_action()\r\n\r\n # Take a step in the environment\r\n next_state, reward, done = env.step(action)\r\n\r\n # Do something with the results\r\n\r\n\r\n[Output 1](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output1.png)\r\n[Output 2](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output2.png)\r\n[Output 3](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output3.png)\r\n[Output 4](https://github.com/ukoksoy/rlenvironments/blob/main/rlenvironments/target_seeker_images/output4.png)\r\n\r\n",
"bugtrack_url": null,
"license": "",
"summary": "Python library for target seeking environment",
"version": "0.2.2",
"project_urls": {
"Homepage": "https://github.com/ukoksoy/rlenvironments"
},
"split_keywords": [
"reinforcement-learning",
"environment",
"target-seeking"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "2f7049b843b110feee3185e8f6124201e8392c6c9e26ccb432a6fb920ec82e32",
"md5": "d53b1cb2063843b237a15cd526ec52e8",
"sha256": "6fbf948e52d2d4bf036d40aa9d42c1e938d003401e13542c260e18da0e8080a9"
},
"downloads": -1,
"filename": "rlenvironments-0.2.2-py3-none-any.whl",
"has_sig": false,
"md5_digest": "d53b1cb2063843b237a15cd526ec52e8",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.7",
"size": 1742,
"upload_time": "2023-06-04T22:50:02",
"upload_time_iso_8601": "2023-06-04T22:50:02.616484Z",
"url": "https://files.pythonhosted.org/packages/2f/70/49b843b110feee3185e8f6124201e8392c6c9e26ccb432a6fb920ec82e32/rlenvironments-0.2.2-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "5839288e86308206735505ab444b7554b3755165fc167921da090214c2a6a7be",
"md5": "4425c00ff76466bf0df4e5744971e5c6",
"sha256": "5701d04337fc79b11c3fb30fb38b8fcd2f43d25d975fca2e466e4e98d13871c9"
},
"downloads": -1,
"filename": "rlenvironments-0.2.2.tar.gz",
"has_sig": false,
"md5_digest": "4425c00ff76466bf0df4e5744971e5c6",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.7",
"size": 1749,
"upload_time": "2023-06-04T22:50:04",
"upload_time_iso_8601": "2023-06-04T22:50:04.652128Z",
"url": "https://files.pythonhosted.org/packages/58/39/288e86308206735505ab444b7554b3755165fc167921da090214c2a6a7be/rlenvironments-0.2.2.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-06-04 22:50:04",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "ukoksoy",
"github_project": "rlenvironments",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "rlenvironments"
}
JSON
