Value-based methods. Apply deep learning architectures to reinforcement learning tasks. Train your own agent that navigates a virtual world from sensory data.
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Updated
Apr 22, 2020 - Jupyter Notebook
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fixed-q-targets
Here are 3 public repositories matching this topic...
Used Vizdoom API to train AI-Bot using DQN, DRQN and add a lot of improvements fixed-Q, Dueling, Prioritzing to maximize K/D of Bot.
reinforcement-learning
tensorflow
artificial-intelligence
vizdoom
actor-critic
dueling-dqn
fixed-q-targets
dqn-tensorflow
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May 3, 2020 - Python
A RL agent that learns to play doom's deadly corridor based on DDQN and PER.
reinforcement-learning
q-learning
deep-q-learning
dueling-network-architecture
pytorch-implmention
prioritized-experience-replay
off-policy
experience-replay
fixed-q-targets
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Updated
Dec 21, 2018 - Python
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