qlearningaction: qlearningaction
In labressler/QLearning: Reinforcement Learning using the Q Learning Algorithm
Description
Usage
Arguments
Details
Value
Note
Author(s)
References
Description
This repository implements Q-Learning, a model-free form of reinforcement learning in R.
Usage
1
qlearningaction(q, currentstate, exploration=.5)
Arguments
q
Input state/action matrix.
currentstate
Current state of the game. Does not have to match any of the state for q.
exploration
The probability of choosing a random state, rather than the one with the highest EV. Default 0.5.
Details
For internal use for qlearn.
Value
An action to take, taken from the possible actions of q.
Note
Contact at liam.bressler@yale.edu
Author(s)
Liam Bressler
References
http://labressler.github.io/analytics
labressler/QLearning documentation built on May 20, 2019, 7:32 p.m.
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Description Usage Arguments Details Value Note Author(s) References
Description
This repository implements Q-Learning, a model-free form of reinforcement learning in R.
Usage
1 | qlearningaction(q, currentstate, exploration=.5)
|
Arguments
q
|
Input state/action matrix. |
currentstate
|
Current state of the game. Does not have to match any of the state for q. |
exploration
|
The probability of choosing a random state, rather than the one with the highest EV. Default 0.5. |
Details
For internal use for qlearn.
Value
An action to take, taken from the possible actions of q.
Note
Contact at liam.bressler@yale.edu
Author(s)
Liam Bressler
References
http://labressler.github.io/analytics
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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