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Metadata-Version: 1.1 | ||
Metadata-Version: 2.1 | ||
Name: RLkit | ||
Version: 0.1 | ||
Version: 0.2.0 | ||
Summary: A simple RL library. | ||
Home-page: http://github.com/shubhamjha97/RLkit | ||
Author: Shubham Jha | ||
Author-email: jha1shubham@gmail.com | ||
License: MIT | ||
Description: # A simple agent trained to play LunarLander using Policy Gradients | ||
Description: # RLkit: A simple Reinforcement Learning library | ||
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This project is still a work in progress. More algorithms and detailed documentation coming soon :) | ||
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To run the code- | ||
``` | ||
python3 main.py | ||
``` | ||
Currently supported agents- | ||
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1. Random agent | ||
2. REINFORCE (Policy Gradients) | ||
3. DQN | ||
4. DQN with baseline | ||
5. Actor-Critic | ||
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See examples for details on how to use the library. | ||
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Requirements- | ||
``` | ||
gym==0.10.5 | ||
matplotlib==2.2.3 | ||
tensorflow==1.6.0 | ||
tensorflow==1.11.0 | ||
gym==0.10.8 | ||
numpy==1.15.4 | ||
``` | ||
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## New in v0.2 | ||
- Added DQN and DQN with baseline agents | ||
- Added ActorCritic agent | ||
- Added support for various activation functions | ||
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## Upcoming | ||
- Duelling DQN | ||
- Support for logging and plotting | ||
- Support for adding seeds | ||
- Support for custom environments | ||
Platform: UNKNOWN | ||
Classifier: Intended Audience :: Science/Research | ||
Classifier: Natural Language :: English | ||
Classifier: Programming Language :: Python :: 3.6 | ||
Description-Content-Type: text/markdown |
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