High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
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Updated
Nov 14, 2024 - Python
High-quality single file implementation of Deep Reinforcement Learning algorithms with research-friendly features (PPO, DQN, C51, DDPG, TD3, SAC, PPG)
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
ALE indicator for the lightline vim plugin
🌑 Enriching python coding in Vim 🐍
Python Implementation of Zero Shot Learning Algorithms (ALE, DeViSE, ESZSL, SAE, SJE) under ZSLGBU protocol
Teal language support for Vim
Pretty, responsive and smooth defaults for a sane ALE, gets you started in 30 seconds
A custom editor based on NeoVim and inspired from Vim and Emacs to maximise productivity.
A leaderboard of human and machine performance on the Arcade Learning Environment (ALE).
Encrypted search for encrypted ActiveRecord models
VIM configuration and vim plugins managed with vim-plug
An Implementation of Attribute Label Embedding (ALE) method of Zero-Shot Learning
Simple tmLanguage package for syntax highlighting trale grammars.
FEM solver applying mesh from third-party mesh generating software
Reinforcement Learning (RL DQN) / Atari Acrobot, Breakout, and Space Invaders.
ANFIS Non-Linear Regression for Average Localization Error Dataset
Proximal Policy Optimization in PyTorch
Vim integration for protolint. https://github.com/yoheimuta/protolint
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