From 2fd89306c3b8d363364997725170ff7d0cf8fcbe Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Tobias=20D=C3=B6ring?= <tobias.doering@stud.hs-bochum.de>
Date: Wed, 9 Mar 2022 11:11:37 +0100
Subject: [PATCH] added increasing steps
---
EvolutionStrategies/main.py | 13 +++++++++----
EvolutionStrategies/population.py | 2 +-
EvolutionStrategies/walker.py | 14 ++++++++++----
3 files changed, 20 insertions(+), 9 deletions(-)
diff --git a/EvolutionStrategies/main.py b/EvolutionStrategies/main.py
index 402634f..2e9889c 100644
--- a/EvolutionStrategies/main.py
+++ b/EvolutionStrategies/main.py
@@ -10,11 +10,11 @@ POP_SIZE = 50
MUTATION_FACTOR = 0.1 # 0 <= x <= 1
LEARNING_RATE = 0.03 # 0 <= x <= 1
GENS = 10000
-MAX_STEPS = 300 # after 1600 steps the Environment gives us a done anyway.
+MAX_STEPS = 100 # after 1600 steps the Environment gives us a done anyway.
DECAY_ALPHA = True
-VERSION = 100
-TEST_WALKER = True
+VERSION = 101
+TEST_WALKER = False
LOAD_BRAIN = False
RENDER_BEST = False
if TEST_WALKER:
@@ -49,14 +49,17 @@ if __name__ == '__main__':
for gen in range(GENS): # this is our game
start_time = time.time()
print(f'Gen: {gen}')
+ print(f'Steps: {population.max_steps}')
population.mutate()
population.play_episode()
population.evolve()
print("Time for Gen: ", time.time() - start_time)
if gen % 10 == 0:
avg_reward = population.get_walker_stats()
+ population.walker.save()
+ population.walker.save_evo(gen)
if avg_reward > best_avg_reward:
- population.walker.save()
+ population.walker.save('best')
best_avg_reward = avg_reward
print("New best walker found")
avg_rewards.append(avg_reward)
@@ -69,6 +72,8 @@ if __name__ == '__main__':
if gen == 5000 and DECAY_ALPHA:
population.lr = 0.005
population.mutation_factor = 0.01
+ # increase the amount of steps the agent can do
+ population.max_steps += 2
plot_reward(avg_rewards)
except KeyboardInterrupt:
diff --git a/EvolutionStrategies/population.py b/EvolutionStrategies/population.py
index 4966214..66e9acc 100644
--- a/EvolutionStrategies/population.py
+++ b/EvolutionStrategies/population.py
@@ -38,7 +38,7 @@ class Population:
for i in range(self.size):
for k in weights:
weights_change = np.dot(self.mutants[i].weights[k].T, A[i]).T
- weights[k] = weights[k] + self.lr/(self.size*self.lr) * weights_change
+ weights[k] = weights[k] + self.lr/(self.size*self.mutation_factor) * weights_change
self.walker.set_weights(weights)
for mutant in self.mutants:
mutant.set_weights(weights)
diff --git a/EvolutionStrategies/walker.py b/EvolutionStrategies/walker.py
index bda567f..327b123 100644
--- a/EvolutionStrategies/walker.py
+++ b/EvolutionStrategies/walker.py
@@ -105,12 +105,18 @@ class Walker:
self.env.action_space.shape[0]], [self.weights['W1'], self.weights['W2']])
network.draw(gen)
- def save(self):
+ def save_evo(self, gen):
+ if not os.path.isdir(f'./models/weights_evo{self.version}'):
+ os.mkdir(f'./models/weights_evo{self.version}')
+ with open(f'./models/weights_evo{self.version}/model-pedal{gen}.p', 'wb') as fp:
+ pickle.dump(self.weights, fp)
+
+ def save(self, name = 'current'):
if not os.path.isdir('./models'):
os.mkdir('./models')
- with open('./models/model-pedal%d.p' % self.version, 'wb') as fp:
+ with open(f'./models/model-pedal{self.version}-{name}.p', 'wb') as fp:
pickle.dump(self.weights, fp)
- def load(self):
- with open('./models/model-pedal%d.p' % self.version, 'rb') as fp:
+ def load(self, name = 'current'):
+ with open(f'./models/model-pedal{self.version}-{name}.p', 'rb') as fp:
self.weights = pickle.load(fp)
--
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