public static void Evaluates_to_same_values_as_gridworld_value_table()
{
var gridWorld = new GridWorld();
var rewarder = new NegativeAtNonTerminalStatesGridWorldRewarder();
var policy = new UniformRandomGridWorldPolicy();
var gridValues = new GridWorldValueTable(gridWorld);
var genericValues = new ValueTable <GridWorldState, GridWorldAction>(gridWorld);
gridValues.Evaluate(policy, rewarder);
genericValues.Evaluate(policy, rewarder);
Assert.That(() => AllValuesAreEqual(gridWorld, genericValues, gridValues));
}
public void Evaluates_to_same_values_as_gamblers_value_table()
{
const double probabilityOfHeads = 0.4;
const int dollarsToWin = 100;
var gamblersWorld = new GamblersWorld(probabilityOfHeads, dollarsToWin);
var rewarder = new GamblersWorldRewarder(gamblersWorld);
var policy = new UniformRandomGamblersPolicy();
var gamblersValues = new GamblersValueTable(gamblersWorld);
var genericValues = new ValueTable <GamblersWorldState, GamblersWorldAction>(gamblersWorld);
gamblersValues.Evaluate(policy, rewarder);
genericValues.Evaluate(policy, rewarder);
Assert.That(() => AllValuesAreEqual(gamblersWorld, genericValues, gamblersValues));
}
private static void EvaluatePolicyValues()
{
const double probabilityOfHeads = 0.4;
const int dollarsToWin = 100;
var world = new GamblersWorld(probabilityOfHeads, dollarsToWin);
var rewarder = new GamblersWorldRewarder(world);
Console.WriteLine("Optimal policy:");
var(policy, values) = DpPolicyOptimiser.FindOptimalPolicy(world, rewarder);
var evalValues = new ValueTable <GamblersWorldState, GamblersWorldAction>(world);
evalValues.Evaluate(policy, rewarder);
PrintPolicyActions(world, policy);
PrintAllValues(world, values);
// Console.WriteLine("Always stake max policy:");
// var policy = new AlwaysStakeMaxPolicy(world);
// PrintPolicyActionsAndValues(world, policy, rewarder);
}