public PolicyIterationRecursive(PolicyEvaluationRecursive policyEvaluation)
{
this.policyEvaluation = policyEvaluation;
}
public static void values()
{
LookupPolicy policy = null;
State<Double> S = new State<Double>(3, 3, 0);
MDP mdp1 = new MDP(S.getCells(), S.getCellAt(1, 1), new ActionsFunction(S),
new TransitionProbabilityFunction(S),
new RewardFunction());
State<Double> S1 = new State<Double>(3, 3, 0);
S1.getCellAt(1, 1).setContent(-1);
S1.getCellAt(1, 2).setContent(0);
S1.getCellAt(1, 3).setContent(-1);
S1.getCellAt(2, 1).setContent(-2);
S1.getCellAt(2, 2).setContent(1);
S1.getCellAt(2, 3).setContent(-2);
S1.getCellAt(3, 1).setContent(-3);
S1.getCellAt(3, 2).setContent(2);
S1.getCellAt(3, 3).setContent(-3);
MDP mdp2 = new MDP(S1.getCells(), S1.getCellAt(1, 1), new ActionsFunction(S1),
new TransitionProbabilityFunction(S1),
new RewardFunction());
State<Double> S2 = new State<Double>(3, 3, 0);
// double r = -100;
double epsilon = 0.00001;
S2.getCellAt(1, 1).setContent(1);
S2.getCellAt(1, 2).setContent(0);
S2.getCellAt(1, 3).setContent(-1);
S2.getCellAt(2, 1).setContent(2);
S2.getCellAt(2, 2).setContent(-1);
S2.getCellAt(2, 3).setContent(-2);
S2.getCellAt(3, 1).setContent(3);
S2.getCellAt(3, 2).setContent(-2);
S2.getCellAt(3, 3).setContent(-3);
MDP mdp = new MDP(S2.getCells(), S2.getCellAt(1, 1), new ActionsFunction(S2),
new TransitionProbabilityFunction(S2),
new RewardFunction());
PolicyEvaluationRecursive pev = new PolicyEvaluationRecursive(1000, epsilon);
PolicyIterationRecursive pi = new PolicyIterationRecursive(pev);
policy = pi.policyIteration(mdp, mdp1, mdp2);
foreach (var s in S.getCells())
{
try
{
CS8803AGA.PsychSim.State.Action a = policy.action(s);
Console.Write(s.getX() + " " + s.getY() + ": ");
Console.WriteLine(a.i);
Console.WriteLine();
}
catch (Exception e)
{
}
}
}
