Keras implementation of DQN on ViZDoom environment
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Updated
Oct 16, 2016 - Python
Keras implementation of DQN on ViZDoom environment
submission to TTI-Chicago programming requirement
deep reinforcement learning research
Reinforcement learning in 3D.
realisation of reinforcement learning algorithms based with vizdoom
The docker builder for tensorflow and vizdoom
😺 Imitation Learning based on A3C algorithm 🛠
Reinforcement Learning in Keras on VizDoom
C51-DDQN in Keras
Direct Future Prediction (DFP ) in Keras
😈 Train ViZDoom agents by Reinforcement Learning 👻
A2C, ACKTR and A2T implementations for ViZDoom
PyOblige is Python wrapper for OBLIGE - random level generator for Doom
Playing FPS Game with Supervised Learning
05-06 Ekim tarihlerinde gerçekleşen DeepCon konferansındaki Derin Pekiştirmeli Öğrenme Atölyesi
😅 Progressive Neural Network, based on A3C to train agents on ViZDoom scenarios
This research project investigated Bio-Inspired Neural Network capabilities and State-of-the-Art implementations. As an experiment, it uses ViZDoom; a Doom-based AI Research Platform for Reinforcement Learning from Raw Visual Information.
Continual Reinforcement Learning in 3D Non-stationary Environments
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