public static void EstimateStateValuesWithTd0()
{
var env = new RandomWalkEnvironment(5, 3);
var actualValues = new[]
{
1.0 / 6,
2.0 / 6,
3.0 / 6,
4.0 / 6,
5.0 / 6
};
var estimator = new Td0ValueEstimator();
var estimates10 = estimator.Estimate(env, 10);
var estimates100 = estimator.Estimate(env, 100);
var estimates1000 = estimator.Estimate(env, 1000);
var plotter = new Plotter();
var plt = plotter.Plt;
plt.Title("TD0 random walk estimates after X episodes");
double[] dataX = { 1, 2, 3, 4, 5 };
plt.PlotScatter(dataX, actualValues, label: "actual");
plt.PlotScatter(dataX, estimates10, label: "10");
plt.PlotScatter(dataX, estimates100, label: "100");
plt.PlotScatter(dataX, estimates1000, label: "1000");
plt.Legend();
plotter.Show();
}
private static void CompareMcAndTd0()
{
var env = new RandomWalkEnvironment(5, 3);
var actualValues = new[]
{
1.0 / 6,
2.0 / 6,
3.0 / 6,
4.0 / 6,
5.0 / 6
};
var mcEstimator = new McValueEstimator();
var td0ValueEstimator05 = new Td0ValueEstimator(0.05);
var td0ValueEstimator10 = new Td0ValueEstimator(0.10);
var td0ValueEstimator20 = new Td0ValueEstimator(0.20);
var avgMcErrors = new double[100];
var avgTdErrors05 = new double[100];
var avgTdErrors10 = new double[100];
var avgTdErrors20 = new double[100];
for (var i = 0; i < 100; i++)
{
var mcErrors = new double[100];
var tdErrors05 = new double[100];
var tdErrors10 = new double[100];
var tdErrors20 = new double[100];
for (var j = 0; j < 100; j++)
{
var mcEstimates = mcEstimator.Estimate(env, i);
var tdEstimates05 = td0ValueEstimator05.Estimate(env, i);
var tdEstimates10 = td0ValueEstimator10.Estimate(env, i);
var tdEstimates20 = td0ValueEstimator20.Estimate(env, i);
mcErrors[j] = AvgRmsError(actualValues, mcEstimates);
tdErrors05[j] = AvgRmsError(actualValues, tdEstimates05);
tdErrors10[j] = AvgRmsError(actualValues, tdEstimates10);
tdErrors20[j] = AvgRmsError(actualValues, tdEstimates20);
}
avgMcErrors[i] = mcErrors.Average();
avgTdErrors05[i] = tdErrors05.Average();
avgTdErrors10[i] = tdErrors10.Average();
avgTdErrors20[i] = tdErrors20.Average();
}
var plotter = new Plotter();
var plt = plotter.Plt;
plt.Title("MC and TD0 RMS error vs num episodes");
var dataX = Enumerable.Range(0, 100).Select(x => (double)x).ToArray();
plt.PlotScatter(dataX, avgMcErrors, label: "mc");
plt.PlotScatter(dataX, avgTdErrors05, label: "td, learning rate: 0.05");
plt.PlotScatter(dataX, avgTdErrors10, label: "td, learning rate: 0.10");
plt.PlotScatter(dataX, avgTdErrors20, label: "td, learning rate: 0.20");
plt.Legend(location: legendLocation.upperRight);
plotter.Show();
}