danaugrs

WARNING: [Loader Message] Code 0 : ReadDataFilesInRegistry: Registry lookup failed to get layer manifest files.
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VULKANINFO
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Vulkan Instance Version: 1.1.114



Instance Extensions:

danaugrs

WARNING: [Loader Message] Code 0 : ReadDataFilesInRegistry: Registry lookup failed to get layer manifest files.
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VULKANINFO
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Vulkan Instance Version: 1.1.114



Instance Extensions:

danaugrs

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VULKANINFO
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Vulkan Instance Version: 1.1.114



Instance Extensions:
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danaugrs

# We will be running multiple concurrent environment instances
instances = 16

# Create a policy for each instance with a different distribution for epsilon
policy = [hk.policy.Greedy()] + [hk.policy.GaussianEpsGreedy(eps, 0.1) for eps in np.arange(0, 1, 1/(instances-1))]

# Create Advantage Actor-Critic agent
agent = hk.agent.A2C(model, actions=dummy_env.action_space.n, nsteps=2, instances=instances, policy=policy)

# Create simulation, train and then test

danaugrs

from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Dense
import huskarl as hk
import gym

# Setup gym environment
create_env = lambda: gym.make('CartPole-v0').unwrapped
dummy_env = create_env()

# Build a simple neural network with 3 fully connected layers as our model