Description Usage Arguments Details Value Note Author(s) References
This repository implements Q-Learning, a model-free form of reinforcement learning in R.
1 2 | qlearningupdate(q, currentstate, currentaction, currentreward, nextstate=NULL,
rewardcount=.5, gamma=.25)
|
q
|
Input state/action matrix. |
currentstate
|
Current state of the game. Does not have to match any of the state for q. |
currentaction
|
Action to take. |
currentreward
|
Reward for currentaction in current iteration. |
nextstate
|
State that the game is in after taking currentaction. |
rewardcount
|
Regularization constant for reward. |
gamma
|
Learning rate constant for Q-Learning. |
For internal use for qlearn.
An updated state/action matrix.
Contact at liam.bressler@yale.edu
Liam Bressler
http://labressler.github.io/analytics
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