Lightweight reinforcement learning experimentation toolkit
Project description
rlexp
A lightweight reinforcement learning experimentation toolkit.
Installation
pip install rlexp-rohanajay
USAGE:
from rlexp import BanditEnv, EpsilonGreedyAgent, Experiment
env = BanditEnv(arms=[0.1, 0.5, 0.9]) agent = EpsilonGreedyAgent(epsilon=0.1, n_arms=3) exp = Experiment(env, agent) exp.run(episodes=1000) exp.plot_rewards()
Features:
- Multi-armed bandit environment
- Epsilon-greedy agent
- Reward tracking and plotting
- No dependencies beyond matplotlib
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Filter files by name, interpreter, ABI, and platform.
If you're not sure about the file name format, learn more about wheel file names.
Copy a direct link to the current filters
File details
Details for the file rlexp_rohanajay-0.0.1.tar.gz.
File metadata
- Download URL: rlexp_rohanajay-0.0.1.tar.gz
- Upload date:
- Size: 2.9 kB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
ae6949c8af11c372cc3d52c3662349c500ff82a9735de3a56096fb50f21c9117
|
|
| MD5 |
9c11eec76c9d3b2e1f89cc0042de323d
|
|
| BLAKE2b-256 |
8938941b109278cc0ee0fa81aa247cd60f728fb975e63788576038e285e433ab
|
File details
Details for the file rlexp_rohanajay-0.0.1-py3-none-any.whl.
File metadata
- Download URL: rlexp_rohanajay-0.0.1-py3-none-any.whl
- Upload date:
- Size: 3.6 kB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.2.0 CPython/3.13.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
3165acd430a7381ac3f44c429f023a7ae94f216c4c37ae6584e08c8334f7b4f1
|
|
| MD5 |
64ace6b464e447299170bf4e0a6d6334
|
|
| BLAKE2b-256 |
7a8e717b6411b2eb08b63007e651c18b6036e4f0e588c2ca1890d6ecbe318274
|
