In skranz/StratTourn: Tournament of game theoretic strategies

library(StratTourn)
library(xtable)
library(ggplot2)
library(reshape2)
library(googleVis)
library(tidyr)

library(StratTourn)
library(xtable)
library(shiny)
library(dplyr)
setwd("D:/libraries/StratTourn/studies")

name = "Tourn_Noisy_PD_20141020_170203"
tourn = load.tournament(paste0(name,".tou"))
# Data for each match
md = tourn$dt
md = add.other.var(md,c("strat","u"))
md$delta.u = md$u - md$other.u
# Names of all strategies
strats = unique(md$strat)

# Data for each round
file = paste0(name,"_rs.csv")
rd = fread(file)
rd = as.tbl(as.data.frame(rd))
rd = add.other.var(rd,c("strat","u"))

# Names of all strategies
strats = unique(rd$strat)

# Perhaps select a subset of strategies
used.strats = strats
ard = rd
if (!identical(used.strats,strats)) {
  rows = rd$strat %in% used.strats & rd$other.strat %in% used.strats
  rd = ard[rows,]
}

end.t = 150
start.t = 1

Average performance each strategy against itself over time

  restore.point("payoffs.over.time.within.report")
  srd = filter(rd, strat==other.strat)
  td = summarise(group_by(srd,strat,t), u=mean(u), num.obs = length(t))
  td = as.data.frame(td)
  t.seq = start.t:min(max(td$t),end.t)
  tsd = do(group_by(td, strat),
    get.smoothed.vals(.,xout=t.seq, xvar="t",yvar=c("u"), wvar="num.obs", spar=0.2))
  tsd$Strat = tsd$strat
  tsd$t = tsd$t+1900
  state = '
  {"nonSelectedAlpha":0.4,"duration":{"multiplier":1,"timeUnit":"Y"},"sizeOption":"_UNISIZE","uniColorForNonSelected":false,"xZoomedDataMin":-2177452800000,"yLambda":1,"time":"1951","playDuration":15000,"colorOption":"2","showTrails":false,"yZoomedDataMin":-0.4,"xZoomedIn":false,"orderedByX":false,"orderedByY":false,"xZoomedDataMax":-599616000000,"xLambda":1,"yZoomedIn":false,"yZoomedDataMax":16,"yAxisOption":"3","iconType":"LINE","xAxisOption":"_TIME","dimensions":{"iconDimensions":["dim0"]}}
  '

  tsd = as.data.frame(tsd)
  tsd$const = 1
  tsd$const2 = 1
  p = gvisMotionChart(tsd, idvar = "Strat", timevar = "t", xvar = "u",
    yvar = "u", colorvar = "strat", sizevar = "const", 
    options = list(state=state))
  #plot(p)
  print(p, tag="chart")

We show the payoffs of each strategy against itself. Note that we have fewer observations for later periods t (see plot below).

t.obs = tabulate(srd$t) / 2
plot(t.obs, xlab="t",ylab="matches (log scale)",main="Number of matches with a period t",log="y")
grid(nx = NA, ny = NULL, col = "lightgray", lty = "dotted",
     lwd = par("lwd"), equilogs = TRUE)