qlearn {QLearning} | R Documentation |
qlearn
Description
Input a game that has variables statevars (which the player can keep track of). The player can perform any of possibleactions. The output matrix will give the expected value of each action (column) in each state (row).
Usage
qlearn(game, statevars, possibleactions, playername="P1",
numiter=1000, prevstrategy=NULL, ...)
Arguments
game |
Name of the game to be played/learned. |
statevars |
A vector of the states to be monitored inside game. These are the conditions under which we the player has to make his decision. |
possibleactions |
A vector of the names of the possible actions inside game. This should be a list of every possible action that can be taken, regardless of state. |
playername |
The name of the variable that holds the name for the player's action inside game. See Details. |
numiter |
Number of iterations of game. Defaults to 50. |
prevstrategy |
Reward matrix returned by a previous qlearn function; serves as a starting point. Defaults to a blank reward matrix. |
... |
Additional arguments to be passed to game. |
Details
At some point in game, there must be a line of the format
playername <- 'Choose'
where playername is substituted with the paramater "playername". This line should be at the point where the user wants to have the player choose an action. Since playername defaults to "P1", it sufficient to put the line:
P1 <- 'Choose'
somewhere in the function.
Value
A matrix describing the expected reward values of performing a certain action (columns) in a certain state (rows).
Note
Contact at liam.bressler@yale.edu
Author(s)
Liam Bressler
References
http://labressler.github.io/analytics
Examples
cardgame <- function()
{
playercards <- sample(1:8,4) #distribute the cards, we're player one
ourcard <- playercards[1] #our card
playertotals <- rep(-1,4) #including the antes
playersinpot <- vector()
for (player in 2:4) #other 3 players go first
{
if (playercards[player]>=2)
{
playertotals[player] <- (-3)
playersinpot <- append(playersinpot,player)
}
}
#the next line is where we want to choose our action
player1 <- 'Choose'
if (player1=="Call")
{
playertotals[1] <- (-3)
playersinpot <- append(playersinpot,1)
}
potsize <- -1*(sum(playertotals)) #the amount in the pot is how much the players put in
playercards[!(1:4 %in% playersinpot)] <- 0 #get rid of everyone who folded
winner <- which.max(playercards) #winner is the person with the highest card who didn't fold
playertotals[winner] <- playertotals[winner]+potsize
return(playertotals[1]) #return how much we won
}
strat <- qlearn(game="cardgame",statevars="ourcard",possibleactions=c("Call","Fold"),
playername="player1",numiter=25000) #make sure each function and variable name is a string
strat