Reinforcement learning is an area of machine learning and computer science concerned with how to select an action in a state that maximizes a numerical reward in a particular environment.
I'm in a course called "Intelligent Machines" at the university. We were introduced with 3 methods of reinforced learning, and with …
machine-learning reinforcement-learning q-learning temporal-differenceAfter training a PyTorch model on a GPU for several hours, the program fails with the error RuntimeError: cuDNN error: …
python pytorch lstm reinforcement-learning dqnI want to setup an RL agent on the OpenAI CarRacing-v0 environment, but before that I want to understand the …
reinforcement-learning openai-gymI am trying to use huber loss in a keras model (writing DQN), but I am getting bad result, I …
python tensorflow keras reinforcement-learning[Note that I am using xvfb-run -s "-screen 0 1400x900x24" jupyter notebook] I try to run a basic set of …
reinforcement-learning openai-gymI know SVMs are supposedly 'ANN killers' in that they automatically select representation complexity and find a global optimum (see …
machine-learning neural-network svm reinforcement-learningI understand that epsilon marks the trade-off between exploration and exploitation. At the beginning, you want epsilon to be high …
machine-learning reinforcement-learning q-learningWhat is the difference between deep reinforcement learning and reinforcement learning? I basically know what reinforcement learning is about, but …
machine-learning reinforcement-learning q-learningI'm using the DQN algorithm to train an agent in my environment, that looks like this: Agent is controlling a …
tensorflow deep-learning reinforcement-learning q-learningI'm using Keras to build a LSTM and tuning it by doing gradient descent with an external cost function. So …
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