prop
prop is a library of Reinforcment Learning agents implemented in pytorch.
Algorithms
| Model | Policy | |
|---|---|---|
| DQN | Model-Free | Off-Policy |
| A2C | Model-Free | On-Policy |
DQN
Deep Q-Learning is a variant of Q-learning with a deep neural network used for estimating Q-values (hence DQN; Deep Q-Network).
Both DQN and DDQN (Double DQN) are implemented.
A2C
Advantage Actor Critic is a variant of Actor-Critic that:
- Uses a neural network to approximate a policy and a value function.
- Computes the advantage of an action to scale the computed gradients. This acts as a vote of confidence (or skepticism) on actions produced by the actor.
Metadata
Release files for rlprop 0.0.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| rlprop-0.0.4.tar.gz | 10.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| rlprop-0.0.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 22.4 kB
Release files / rlprop-0.0.4.tar.gz
| Download URL | rlprop-0.0.4.tar.gz |
|---|---|
| Size | 10.1 kB |
| Tags | Source |
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Release files / rlprop-0.0.4-py3-none-any.whl
| Download URL | rlprop-0.0.4-py3-none-any.whl |
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| Size | 12.3 kB |
| Tags | Python 3 |
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