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https://github.com/mshuqair/reinforcement-learning-grid-world
Implementation of some Reinforcement Learning methods for grid world in Python
https://github.com/mshuqair/reinforcement-learning-grid-world
grid-world monte-carlo python q-learning reinforcement-learning temporal-differencing-learning
Last synced: about 1 month ago
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Implementation of some Reinforcement Learning methods for grid world in Python
- Host: GitHub
- URL: https://github.com/mshuqair/reinforcement-learning-grid-world
- Owner: mshuqair
- License: mit
- Created: 2024-09-11T17:05:30.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2024-09-12T14:20:26.000Z (4 months ago)
- Last Synced: 2024-09-13T04:47:25.624Z (4 months ago)
- Topics: grid-world, monte-carlo, python, q-learning, reinforcement-learning, temporal-differencing-learning
- Language: Python
- Homepage:
- Size: 161 KB
- Stars: 0
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# Reinforcement Learning For Grid World
- Implementation of Reinforcement Learning to solve the Grid World in Python.
- The rest of the documentation is coming soon.
- I plan to use Deep Q-Learning to solve the grid world problem
- The Q-Learning implementation here follows an epsilon greedy with a decay
## Introduction## Definition
## Conclusions
## References
## Code Requirements
The code was run and tested using the following:
- Python 3.10.11
- matplotlib 3.9.0
- seaborn 0.13.2
- numpy 1.26.3