public double getValue(List <int> myhistory, List <int> yourhistory, int action)
{
int nrOfRounds = myhistory.Count();
int roundsAction = 0;
double rewardAction = 0;
// Calculate the sum of payoffs, earned when playing action.
for (int i = 0; i < nrOfRounds; i++)
{
if (myhistory[i] == action)
{
rewardAction += UpdateLogic.getPayoff(myhistory[i], yourhistory[i]);
roundsAction += 1;
}
}
// Returns the average payoff of action.
if (roundsAction == 0)
{
// set the initial estimate to an unrealistic high value to make the probability that each action is tried in the beginning high.
return(6);
}
else
{
return(rewardAction / roundsAction);
}
}
public void createTable()
{
//Clear the score table view
dataGridView.Rows.Clear();
//Create score table
scoreTable = UpdateLogic.scoreTable(nrrounds, nrrestarts, strategies, noise);
initDataGrid();
//Also calls setup
Setup();
}
public double getReward(List <int> myActions, List <int> yourActions)
{
int nrOfRounds = myActions.Count();
double reward = 0;
// This calculates the sum of the rewards earned in each round in history.
for (int i = 0; i < nrOfRounds; i++)
{
reward += UpdateLogic.getPayoff(myActions[i], yourActions[i]);
}
return(reward);
}
//Event called every tick
private void TickTimer_Tick(object sender, EventArgs e)
{
//Update proportions for next time step using replicator equation
allproportions = UpdateLogic.replicator(allproportions, scoreTable, birthrate);
tickCount++;
this.tickLabel.Text = String.Format("Ticks = {0}", tickCount);
//Update plot
updatePlot();
//Update proportions in textbox
updateTextBox();
}
public int getAction(List <int> myhistory, List <int> yourhistory)
{
int action = 0;
// Find the number of times the opponent defected and the total number of played rounds.
int timesOpponentDefect = yourhistory.FindAll(x => x == 1).Count();
int nrOfPlayedRounds = yourhistory.Count();
if (nrOfPlayedRounds > 0)
{
// Calculate the mixed strategy of your opponent.
double[] opponentStrategy = { 1 - (timesOpponentDefect / nrOfPlayedRounds), (timesOpponentDefect / nrOfPlayedRounds) };
// Calculate the expected reward of your actions, given the strategy of the opponent.
double expectedRewardDefect = opponentStrategy[0] * UpdateLogic.getPayoff(1, 0) + opponentStrategy[1] * UpdateLogic.getPayoff(1, 1);
double expectedRewardCooperate = opponentStrategy[0] * UpdateLogic.getPayoff(0, 0) + opponentStrategy[1] * UpdateLogic.getPayoff(0, 1);
// Choose an action proportional to the expected reward of that action.
double probabilityDefect = expectedRewardDefect / (expectedRewardDefect + expectedRewardCooperate);
action = randomAction.proportionalAction(probabilityDefect);
}
return(action);
}
