Asynchronous Method for Deep Reinforcement Learning
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Updated
Oct 18, 2017 - Python
Asynchronous Method for Deep Reinforcement Learning
Implementing DeepMind's Fast Reinforcement Learning paper, and adding additional features to generalize the algorithms
An implementation of the Differential Neural Computer (DNC) in TensorFlow
Open-zero is a research project aiming to realize the various projects of the company DeepMind
hyper optimized alpha zero implementation to play gomoku (distributed training with ray, mcts with cython)
Keras and PyTorch implementations for Google's WaveNet
A TensorFlow implementation of DeepMind's WaveNet paper
RocAlphaGo with date of death of Samatha Smith in Python 3.x
Unofficial code for the deep reinforcement model Agent57.
PyTorch Implementation of Relation Network on Sort-of-CLEVR Dataset
Implementation based on DeepMind's paper: Neural Episodic Control using tensorflow.
Farama Gymnasium API Wrapper for the DeepMind Control Suite and DeepMind Robot Manipulation Tasks
Applying PBT optimization technique to different domains
Delusions in sequence models for interaction and control
✭ MAGNETRON TECHNOLOGY ™ ✭: AlphaStar has the same kind of constraints that humans play under – including viewing the world through a camera, which makes it ideal to adapt to ARTIFICIAL INTELLIGENCE 2.0 ™ for DRONEBOT ™ and QUEEN ™ of PHALANX ™/HIVE ™/SWARM ™ (see ARTIFICIAL INTELLIGENCE 2.0 ™ Documentation). AlphaStar is the first AI to reach t…
TensorFlow implementation of the two 1-step methods from "Asynchronous Deep Reinforcement Learning Methods" by Mnih et. al., 2016 for OpenAIs Gym-environment.
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