//Two basic functions for the Monster engine
actionDecision think(Enemy monster)
{
float[] ratings = new float[(int)actionDecision.NUM_ACTIONS];
int dist_x = game_state.local_player.getX() - monster.getX();
int dist_y = game_state.local_player.getY() - monster.getY();
int Dp = GetRating(Math.Sqrt(Math.Pow(dist_x, 2) + Math.Pow(dist_y, 2)), 800.0f);
int Db = 0; //Bullet system not in yet
int Alg = 0;
if (Math.Abs(dist_x) < Math.Abs(dist_y))
{
Alg = GetRating(Math.Abs(dist_x), 400);
}
else
{
Alg = GetRating(Math.Abs(dist_y), 240);
}
int Hlt = GetRating(monster.getHealth(), monster.getMaxHealth());
actionDecision retval = actionDecision.FLEE;
float max_value = 0;
for (int i = 0; i < (int)actionDecision.NUM_ACTIONS; ++i)
{
ratings[i] =
decision_matrix[(int)monster.getType(), i, (int)actionFactor.DP] * Dp +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.DB] * Db +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.AL] * Alg +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.HL] * Hlt;
if (ratings[i] > max_value)
{
retval = (actionDecision)i;
max_value = ratings[i];
}
}
if (max_value < 5)
{
return(actionDecision.IDLE);
}
return(retval);
}
//Two basic functions for the Monster engine
actionDecision think(Enemy monster)
{
float[] ratings = new float[(int)actionDecision.NUM_ACTIONS];
int dist_x = game_state.local_player.getX() - monster.getX();
int dist_y = game_state.local_player.getY() - monster.getY();
int Dp = GetRating(Math.Sqrt(Math.Pow(dist_x, 2) + Math.Pow(dist_y, 2)), 800.0f);
int Db = 0; //Bullet system not in yet
int Alg = 0;
if (Math.Abs(dist_x) < Math.Abs(dist_y))
{
Alg = GetRating(Math.Abs(dist_x), 400);
}
else
{
Alg = GetRating(Math.Abs(dist_y), 240);
}
int Hlt = GetRating(monster.getHealth(), monster.getMaxHealth());
actionDecision retval = actionDecision.FLEE;
float max_value = 0;
for (int i = 0; i < (int)actionDecision.NUM_ACTIONS; ++i)
{
ratings[i] =
decision_matrix[(int)monster.getType(), i, (int)actionFactor.DP]*Dp +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.DB]*Db +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.AL]*Alg +
decision_matrix[(int)monster.getType(), i, (int)actionFactor.HL]*Hlt;
if (ratings[i] > max_value)
{
retval = (actionDecision)i;
max_value = ratings[i];
}
}
if (max_value < 5)
{
return actionDecision.IDLE;
}
return retval;
}