Stars
A minimalist environment for decision-making in autonomous driving
Revisiting Discrete Soft Actor-Critic Accepted by Transactions on Machine Learning Research (TMLR)
Supplementary Data for Evolving Reinforcement Learning Algorithms
⭐️ NLP Algorithms with transformers lib. Supporting Text-Classification, Text-Generation, Information-Extraction, Text-Matching, RLHF, SFT etc.
Jax and Torch Multi-Agent SAC on PettingZoo 8000 API
AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
Transfer Learning for Related Reinforcement Learning Tasks via Image-to-Image Translation
Codebase for Generative Adversarial Imputation Networks (GAIN) - ICML 2018
A collection of multi agent environments based on OpenAI gym.
Hello, I pushed some python environments for Multi Agent Reinforcement Learning.
PyTorch Implementation of "Distilling a Neural Network Into a Soft Decision Tree." Nicholas Frosst, Geoffrey Hinton., 2017.
PyTorch Implementation of MADDPG (Lowe et. al. 2017)
Deep Q-Learning RL Cartpole Implementation for Soft Decision Trees
Neural-Backed Decision Tree sample integration with pytorch-image-models
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Implementations of IQL, QMIX, VDN, COMA, QTRAN, MAVEN, CommNet, DyMA-CL, and G2ANet on SMAC, the decentralised micromanagement scenario of StarCraft II
Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.
AlexeyAB / darknet
Forked from pjreddie/darknetYOLOv4 / Scaled-YOLOv4 / YOLO - Neural Networks for Object Detection (Windows and Linux version of Darknet )
D2Det: Towards High Quality Object Detection and Instance Segmentation (CVPR2020)
OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.
Source code for the dissertation: "Multi-Pass Deep Q-Networks for Reinforcement Learning with Parameterised Action Spaces"
Parametrized Deep Q-Networks Learning: Reinforcement Learning with Discrete-Continuous Hybrid Action Space