private float[] V; // value per state
// Start is called before the first frame update
void Start()
{
lineworld = new LineWorld();
Pi = Algorithms.create_random_uniform_policy(lineworld.S.Length, lineworld.A.Length); //
V = Algorithms.iterative_policy_evaluation(lineworld.S, lineworld.A, lineworld.T, lineworld.P, lineworld.R, Pi);
UIDisplayator.AddVF("Value Function de la stratégie \"random uniform\"", ref V);
////////////////////////////////////////////////////////////////////////////////////////
for (int i = 0; i < lineworld.S.Length; ++i)
{
for (int y = 0; y < lineworld.A.Length; ++y)
{
Pi[i, y] = 0.0f;
}
}
for (int i = 0; i < lineworld.S.Length; ++i)
{
Pi[i, 1] = 1.0f;
}
V = Algorithms.iterative_policy_evaluation(lineworld.S, lineworld.A, lineworld.T, lineworld.P, lineworld.R, Pi);
UIDisplayator.AddVF("Value Function de la stratégie \"tout a droite\"", ref V);
PairVPi VPi = Algorithms.policy_iteration(lineworld.S, lineworld.A, lineworld.T, lineworld.P, lineworld.R);
UIDisplayator.AddVF("La value function optimale", ref VPi.V);
Debug.Log("La policy optimale : ");
for (int s = 0; s < lineworld.S.Length; ++s)
{
for (int a = 0; a < lineworld.A.Length; ++a)
{
Debug.Log("S=" + s + " A=" + a + " =" + VPi.Pi[s, a]);
}
}
/////////////////////////////////////////////////////////////////////////////////////
gridworld = new GridWorld();
Pi = Algorithms.create_random_uniform_policy(gridworld.S.Length, gridworld.A.Length); //
V = Algorithms.iterative_policy_evaluation(gridworld.S, gridworld.A, gridworld.T, gridworld.P, gridworld.R, Pi);
UIDisplayator.AddVF("Value Function de la stratégie \"random uniform\"", ref V);
////////////////////////////////////////////////////////////////////////////////////////
for (int i = 0; i < gridworld.S.Length; ++i)
{
for (int y = 0; y < gridworld.A.Length; ++y)
{
Pi[i, y] = 0.0f;
}
}
for (int i = 0; i < gridworld.S.Length; ++i)
{
Pi[i, 1] = 1.0f;
}
V = Algorithms.iterative_policy_evaluation(gridworld.S, gridworld.A, gridworld.T, gridworld.P, gridworld.R, Pi);
UIDisplayator.AddVF("Value Function de la stratégie \"tout a droite\"", ref V);
VPi = Algorithms.policy_iteration(gridworld.S, gridworld.A, gridworld.T, gridworld.P, gridworld.R);
UIDisplayator.AddVF("La value function optimale", ref VPi.V);
Debug.Log("La policy optimale : ");
for (int s = 0; s < gridworld.S.Length; ++s)
{
for (int a = 0; a < gridworld.A.Length; ++a)
{
Debug.Log("S=" + s + " A=" + a + " =" + VPi.Pi[s, a]);
}
}
//////////////////////////////////////////////////
float[,] Q = Algorithms.monte_carlo_control_with_exploring_starts(
lineworld.S, lineworld.A, lineworld.T, lineworld.step, lineworld.step_until_the_end_of_episode_and_return_transitions, out Pi, 0.99f, 5000
);
Debug.Log("L'action value optimale :");
for (int s = 0; s < lineworld.S.Length; ++s)
{
for (int a = 0; a < lineworld.A.Length; ++a)
{
Debug.Log("S:" + s + " A:" + a + " Q:" + Q[s, a]);
}
}
Debug.Log("La policy \"optimale\" :");
for (int s = 0; s < lineworld.S.Length; ++s)
{
for (int a = 0; a < lineworld.A.Length; ++a)
{
Debug.Log("S:" + s + " A:" + a + " Pi:" + Pi[s, a]);
}
}
}
void Awake()
{
instance = this;
VFs = new List <float[]>();
}
