question

@mark zhen, in the model you supplied, your reward function is as follows:

double reward = Model.find("Sink1").avgTardiness;

if (reward < 0.50) {
    reward = -1.0;
} else if (reward > 0.50) {
    reward = 1.0;
} else if (reward > 0.55) {
   reward = 3.0;
} else if (reward > 0.60) {
    reward = 7.0;
}

int done= Model.time > 18000;
return [reward, done];

You have a process flow that writes the avgTardiness value to a table; the sink then gets that value from the table and sets it as the reward.

That avgTardiness is the equation:

Model.find("Sink1").totalTardiness / Model.find("Sink1").as(Object).stats.input.value;

Essentially averaging the total Tardinesses. The initial value is 0. Because of that, the first few times the processors use their Pull Strategy, they get a -1 reward because avgTardiness on the sink is 0.

The first item that enters the sink has a Total Tardiness of -6910. So, every time a processor does a Pull Strategy call, it will have a -1 reward. After running the model to the end, every tardiness value I saw was negative, meaning the average was always negative, and so the reward is always -1. That's why you get such a large negative number for your reward total at the end.