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.
In reinforcement learning, what is the difference between policy iteration and value iteration? As much as I understand, in value …
machine-learning reinforcement-learning markov-models value-iterationAlthough I know that SARSA is on-policy while Q-learning is off-policy, when looking at their formulas it's hard (to me) …
artificial-intelligence reinforcement-learning q-learning sarsaI'm currently trying to get an ANN to play a video game and and I was hoping to get some …
machine-learning computer-vision neural-network video-processing reinforcement-learningI know the basics of feedforward neural networks, and how to train them using the backpropagation algorithm, but I'm looking …
algorithm language-agnostic machine-learning neural-network reinforcement-learningI've seen such words as: A policy defines the learning agent's way of behaving at a given time. Roughly speaking, …
machine-learning terminology reinforcement-learning markov-decision-processI'm trying to get an agent to learn the mouse movements necessary to best perform some task in a reinforcement …
algorithm machine-learning reinforcement-learning q-learningI have recently been working on a project that uses a neural network for virtual robot control. I used tensorflow …
python parallel-processing multiprocessing tensorflow reinforcement-learningϵ-greedy policy I know the Q-learning algorithm should try to balance between exploration and exploitation. Since I'm a beginner in …
machine-learning reinforcement-learning q-learningI know the basics of Reinforcement Learning, but what terms it's necessary to understand to be able read arxiv PPO …
machine-learning reinforcement-learningHow is Q-learning different from value iteration in reinforcement learning? I know Q-learning is model-free and training samples are transitions (…
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