diff --git a/EvolutionStrategies/main.py b/EvolutionStrategies/main.py
index aa9e09f05c574d8846700164912f585d8f5c5031..d8c8a50521a4b13ec9edfb04cab71985bf6d436b 100644
--- a/EvolutionStrategies/main.py
+++ b/EvolutionStrategies/main.py
@@ -4,14 +4,14 @@ import matplotlib.pyplot as plt
import pickle
import sys
-HIDDEN_LAYER = 2
-BIAS = True
+HIDDEN_LAYER = 12
+BIAS = False
POP_SIZE = 50
MUTATION_FACTOR = 0.1 # 0 <= x <= 1
LEARNING_RATE = 0.03 # 0 <= x <= 1
GENS = 7000
-MAX_STEPS = 200 # after 1600 steps the Environment gives us a done anyway.
-
+MAX_STEPS = 300 # after 1600 steps the Environment gives us a done anyway.
+DECAY_ALPHA = True
VERSION = 1
TEST_WALKER = True
@@ -58,10 +58,12 @@ if __name__ == '__main__':
population.walker.save_mlp_weights(gen)
with open(f'./models/{HIDDEN_LAYER}_{VERSION}_{POP_SIZE}_{LEARNING_RATE}_AvgRewards', 'wb') as fp:
pickle.dump(avg_rewards, fp)
- if gen == 1000:
+ if gen == 1000 and DECAY_ALPHA:
population.lr = 0.01
- #if gen == 5000:
- #population.lr = 0.005
+ population.mutation_factor = 0.05
+ if gen == 5000 and DECAY_ALPHA:
+ population.lr = 0.005
+ population.mutation_factor = 0.01
plot_reward(avg_rewards)
except KeyboardInterrupt:
diff --git a/EvolutionStrategies/population.py b/EvolutionStrategies/population.py
index 0c4824773c5f8e5fe5b1b17c9e1015cdee4b225d..49662149501f63cc80b4a914aab3a4520f2d5723 100644
--- a/EvolutionStrategies/population.py
+++ b/EvolutionStrategies/population.py
@@ -14,7 +14,7 @@ class Population:
self.version = version
self.max_steps = max_steps
self.render_best = render_best
- self.env = gym.make('Pendulum-v1') # MountainCarContinuous-v0 LunarLanderContinuous-v2 Pendulum-v1 CarRacing-v0
+ self.env = gym.make('BipedalWalker-v3') # MountainCarContinuous-v0 LunarLanderContinuous-v2 Pendulum-v1 CarRacing-v0
self.walker = Walker(hidden_layer, bias, version, load_brain, self.env)
self.mutated_weights = dict()
self.mutants = []
diff --git a/MutateActions/5_50_50_0.2.png b/MutateActions/5_50_50_0.2.png
new file mode 100644
index 0000000000000000000000000000000000000000..3494bfc4d920e956b26d8388edc6fc4b7a98dee5
Binary files /dev/null and b/MutateActions/5_50_50_0.2.png differ
diff --git a/MutateActions/main.py b/MutateActions/main.py
index b81ae78277734b51a6bea91463d93f6c8a6139f1..a8d4fe7545d19b013a9bc01b16fa04b411f9bdee 100644
--- a/MutateActions/main.py
+++ b/MutateActions/main.py
@@ -1,7 +1,7 @@
from population import Population
-import time
import matplotlib.pyplot as plt
import pickle
+import sys
INCREASE_BY = 5
BRAIN_SIZE = 50
@@ -17,24 +17,33 @@ if TEST_WALKER:
if __name__ == '__main__':
- population = Population(POP_SIZE, BRAIN_SIZE,MUTATION_FACTOR, LOAD_BRAIN, RENDER_BEST)
-
- rewards = []
-
if TEST_WALKER:
rewards = []
+ steps = []
with open('rewards.p', 'rb') as fp:
rewards = pickle.load(fp)
+ with open('steps.p', 'rb') as fp:
+ steps = pickle.load(fp)
plt.title(f'{POP_SIZE}, {MUTATION_FACTOR}')
plt.xlabel('Episodes')
plt.ylabel('Rewards')
plt.plot(rewards)
+ plt.plot(steps)
plt.savefig(f'./models/{POP_SIZE}, {MUTATION_FACTOR}.png')
plt.show()
+ sys.exit(0)
+
+ population = Population(POP_SIZE, BRAIN_SIZE,MUTATION_FACTOR, LOAD_BRAIN, RENDER_BEST)
+
+ rewards = []
+ steps = []
- while GAME_CANCELLED is False: # this is our game
+ while population.gen < 2000: # this is our game
if population.all_players_finished(): # this is our genetic algorithm after one generation of players
+ rewards.append(population.walkers[0].fitness)
+ steps.append(len(population.walkers[0].brain.directions))
+ print(f'Best Fitness: {population.walkers[0].fitness}')
population.natural_selection()
population.mutate_babies()
population.increase_moves(INCREASE_BY)
@@ -45,11 +54,12 @@ if __name__ == '__main__':
print(f'Best Fitness: {population.fitnesses[population.best_walker_index]}')
print(f'Max Steps: {population.max_steps}')
- rewards.append(population.fitnesses[population.best_walker_index])
if population.gen % 10 == 0:
with open("rewards.p", 'wb') as fp:
pickle.dump(rewards, fp)
+ with open("steps.p", 'wb') as fp:
+ pickle.dump(steps, fp)
else:
population.update()
# time.sleep(0.1)
diff --git a/MutateActions/population.py b/MutateActions/population.py
index f51dcff9a048a12e11fa06d2967e8644d804f196..4f62c2c6118f925b8a849ca6194ee8e5c9b13f35 100644
--- a/MutateActions/population.py
+++ b/MutateActions/population.py
@@ -39,16 +39,12 @@ class Population:
else:
walker.update()
- """def calculate_fitness(self): # calculate the fitness of all players
- for walker in self.walkers:
- walker.calculate_fitness()"""
-
def calculate_fitness_sum(self):
self.fitness_sum = 0
self.fitnesses = np.zeros(self.size)
for i in range(self.size):
self.fitnesses[i] = self.walkers[i].fitness
- self.fitnesses -= np.min(self.fitnesses) # maybe offset: +1
+ self.fitnesses -= np.min(self.fitnesses)
self.fitness_sum = np.sum(self.fitnesses)
def all_players_finished(self): # returns whether all the players are either dead or have reached the goal
@@ -58,8 +54,6 @@ class Population:
return True
def natural_selection(self): # gets the next generation of players
- #for i in range(self.size):
- #new_walkers.append(Walker(self.envs[i], self.brain_size))
self.calculate_fitness_sum()
self.set_best_walker()
self.walkers[self.best_walker_index].brain.save()