Python implementation of the soft Actor-Critic (SAC) algorithm together with training results to complement the published blog post on SAC.
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Updated
Sep 14, 2023 - Python
Python implementation of the soft Actor-Critic (SAC) algorithm together with training results to complement the published blog post on SAC.
Simple pytorch implementations of RL algorithms
SimplySAC replicates Soft-Actor-Critic with minimum (~200) lines of code in clean, readable PyTorch style, while trying to use as few additional tricks and hyper-parameters as possible (MuJoCo and PyBullet benchmarks included).
Autonomous Driving W/ Deep Reinforcement Learning in Lane Keeping - DDQN and SAC with kinematics/birdview-images
Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0
This project seeks to harness sophisticated machine learning techniques for processing EEG and fMRI data, employing programmable magnetic field generators and transcranial ultrasonic stimulation. The initiative is designed to cultivate a shared cognitive domain, analogous to rulial space, through synchronized neural stimulation of participants.
Multi-Agent Robot Learning algorithm using Deep Active Inference (DAI) for road hazard anomaly detection and Soft Actor Critic decomposed for multi-agent settings (mSAC)
Directed reading on Deep Reinforcement Learning
PyTorch framework for reinforcement learning
Mapless navigation in Coppeliasim
A Torch Based RL Framework for Rapid Prototyping of Research Papers
An implementation of the latent-conditioned soft actor-critic algorithm by Osa et al. (2021) used for diverse skill learning.
Tests SOTA algorithms using pendulum as baseline environment
Make Deep Q Learning Fast
Credits to Hyperdog Ros2 for URDF model https://github.com/NDHANA94/hyperdog_ros2, Credits to philtabor for his amazing tutortial on SAC, https://github.com/philtabor/Youtube-Code-Repository/tree/master/ReinforcementLearning/PolicyGradient/SAC
Density estimation based Soft Actor-Critic: deep reinforcement learning for static output feedback control with measurement noise
Evaluating the impact of curriculum learning on the training process for an intelligent agent in a video game
Pytorch implementation of classic and latest Model-Free RL algorithms.
Project for enabling easy and basic Reinforcement Learning by using PyTorch & OpenAI Gym. Currently contains an implementation of the Soft-Actor-Critic algorithm.
Master Thesis Project: Social Learning in Multi-Agent Reinforcement Learning for Carbon Emission Reduction
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