diff --git a/gameobjects.py b/gameobjects.py
index 9c24911..32d641c 100644
--- a/gameobjects.py
+++ b/gameobjects.py
@@ -46,7 +46,7 @@ class GameObject:
         self.image.set_colorkey(None)  # Explicitly disable colorkey
 
 class Horse(GameObject):
-    default_vacceleration = 0.3  # Default acceleration value
+    default_vacceleration = 0.2  # Default acceleration value
     vspeed = 0  # Vertical speed
     vacceleration = 0  # Vertical acceleration
     stopped = False  # Whether the horse is stopped
@@ -106,8 +106,7 @@ class Horse(GameObject):
     def count_fitness(self):
         if self.stopped == False:
             self.fitness += 1
-            if self.vacceleration == 0:
-                self.fitness -= 0.9
+            if self.vspeed == 0: self.fitness -= 0.9
 
 class Background(GameObject):
     def __init__(self, image_path, x, y):
diff --git a/genetic_alg.py b/genetic_alg.py
index 82bc4e0..c5f0bbd 100644
--- a/genetic_alg.py
+++ b/genetic_alg.py
@@ -22,6 +22,9 @@ class GeneticAlgorithm:
         self.percentageBest = percentageBest
         self.percentageNew = percentageNew
         self.inputSize = inputSize
+
+        self.fitnessBest = []
+
         self.device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
         print(self.device)
         self.initialize_population()
@@ -49,11 +52,14 @@ class GeneticAlgorithm:
     def mutate(self, model: NeuralNetwork):
         for param in model.parameters():
             if torch.rand(1).item() < self.mutationRate:
-                param.data += torch.randn_like(param.data) * 0.1 * (1 if torch.rand(1).item() >= 0.5 else -1)
+                param.data += torch.randn_like(param.data) * 0.1
         return model
 
     def learn(self, fitness: list):
-        self.population = [self.population[x] for x in np.argsort(fitness)[::-1]]
+        sortedFitnessArg = np.argsort(fitness)[::-1]
+        self.fitnessBest.append(fitness[sortedFitnessArg[0]])
+        print(self.fitnessBest[-1])
+        self.population = [self.population[x] for x in sortedFitnessArg]
         numBest = int(self.populationSize * self.percentageBest)
         self.population = self.population[:numBest]
         while len(self.population) < self.populationSize - self.populationSize * self.percentageNew:
diff --git a/main.py b/main.py
index 4163487..718b328 100644
--- a/main.py
+++ b/main.py
@@ -3,11 +3,11 @@ import sys
 from gameobjects import *
 from genetic_alg import GeneticAlgorithm
 
-POPULATION_SIZE = 50
+POPULATION_SIZE = 100
 MUTATION_RATE = 0.5
 POPULATION_NEW = 0.1
-POPULATION_BEST = 0.2
-FRAME_RATE = 160  # TODO: FIX THE INCORRECT FRAME RATE CORRELATION
+POPULATION_BEST = 0.3
+FRAME_RATE = 300  # TODO: FIX THE INCORRECT FRAME RATE CORRELATION
 BARRIER_SPEED = 10
 BARRIER_DELAY = 100
 
@@ -60,12 +60,13 @@ def init_game():
     UI.add_horses(horses)
 
 
-def get_features(horse):
+def get_features(horse: Horse):
     features = [last_barrier.rect.topleft[0], last_barrier.rect.topleft[1],
                 last_barrier.rect.bottomright[0], last_barrier.rect.bottomright[1],
                 horse.rect.topleft[0], horse.rect.topleft[1],
                 horse.rect.bottomright[0], horse.rect.bottomright[1],
-                0, HEIGHT, BARRIER_SPEED]
+                0, HEIGHT, horse.vspeed, horse.vacceleration, BARRIER_SPEED]
+    features = [x / HEIGHT for x in features]
     return features