Openai Spaces for a modified environmentActor-Critic in Discrete action spacesQ Learning Neural network for tic tac toe Input implementation probleminverted pendulum REINFORCEWhat is wrong with this reinforcement learning environment ?out of memory error when consrtucting 2d list from 2 numpy arraysReinforcement learning: easily learnable state representationIs RL applicable to environments that are totally RANDOM?Why not use max(returns) instead of average(returns) in off-policy Monte Carlo control?Gym action space for board game with reward functionKeras Loss Value Extremely High + Prediction Result same
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Openai Spaces for a modified environment
Actor-Critic in Discrete action spacesQ Learning Neural network for tic tac toe Input implementation probleminverted pendulum REINFORCEWhat is wrong with this reinforcement learning environment ?out of memory error when consrtucting 2d list from 2 numpy arraysReinforcement learning: easily learnable state representationIs RL applicable to environments that are totally RANDOM?Why not use max(returns) instead of average(returns) in off-policy Monte Carlo control?Gym action space for board game with reward functionKeras Loss Value Extremely High + Prediction Result same
$begingroup$
I have a 2-dimensional array of normalized data. I am using
space = np.array([0,1,...366],[0,0.000001,.....1])
I need to fit this as an observation space in reinforcement learning. I have extended the open ai gym and created a custom made environment. How to fit in this 2-dimensional array in openAI spaces.
Can I use Box, DiscreteSpace or MultiDiscrete space? Can anyone help me with a sample code to fit this in observation space?
python deep-learning reinforcement-learning q-learning openai-gym
New contributor
$endgroup$
add a comment |
$begingroup$
I have a 2-dimensional array of normalized data. I am using
space = np.array([0,1,...366],[0,0.000001,.....1])
I need to fit this as an observation space in reinforcement learning. I have extended the open ai gym and created a custom made environment. How to fit in this 2-dimensional array in openAI spaces.
Can I use Box, DiscreteSpace or MultiDiscrete space? Can anyone help me with a sample code to fit this in observation space?
python deep-learning reinforcement-learning q-learning openai-gym
New contributor
$endgroup$
add a comment |
$begingroup$
I have a 2-dimensional array of normalized data. I am using
space = np.array([0,1,...366],[0,0.000001,.....1])
I need to fit this as an observation space in reinforcement learning. I have extended the open ai gym and created a custom made environment. How to fit in this 2-dimensional array in openAI spaces.
Can I use Box, DiscreteSpace or MultiDiscrete space? Can anyone help me with a sample code to fit this in observation space?
python deep-learning reinforcement-learning q-learning openai-gym
New contributor
$endgroup$
I have a 2-dimensional array of normalized data. I am using
space = np.array([0,1,...366],[0,0.000001,.....1])
I need to fit this as an observation space in reinforcement learning. I have extended the open ai gym and created a custom made environment. How to fit in this 2-dimensional array in openAI spaces.
Can I use Box, DiscreteSpace or MultiDiscrete space? Can anyone help me with a sample code to fit this in observation space?
python deep-learning reinforcement-learning q-learning openai-gym
python deep-learning reinforcement-learning q-learning openai-gym
New contributor
New contributor
edited 9 hours ago
Karthik Rajkumar
New contributor
asked 9 hours ago
Karthik RajkumarKarthik Rajkumar
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113
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New contributor
add a comment |
add a comment |
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