AI Course Project 14032 - Dr. TanGhatari

A simple calculator widget for SAP Analytics Cloud

💅💄 Sistema de Atendimento ao Cliente da empresa BEIBE

Funções de Sistemas de Financiamento comparação Gráfica - SAC, PRICE, SAA - Matplotlib

PyTorch implementation of SAC (Soft Actor-Critic)

Reinforcement learning agents (TD3 & SAC) for AirHockey, exploring the impact of policy noise, delay, and other training variations.

A simple and neat implementation of reinforcement learning algorithms.

Adversarial Patch defense using SegmentAndComplete (SAC) & Masked AutoEncoder (MAE)

Analysis scripts for the manuscript "Spindle checkpoint silencing at kinetochores at submaximal microtubule occupancy" by Etemad et al. "

HomeBrew formulae for building and running SaC on MacOS

Building and training a Furuta Pendulum Robot with an SAC/PPO reinforcement learning implementation

Discrete Soft Actor-Critic with Environment Parallelization, SEER, SAC+AE, SD-SAC and Munchausen Reinforcement Learning

fern - Federated Earthquake data Retrieval via Network

PROJECT MIGRATED TO CODEBERG - Reinforcement Learning in Multiplicative Domains

Reinforcement Learning Agents for Analog Circuit Sizing in Haskell.

Experimental version of Stable Baslines3 which expands SB3 2.2.1 to be able to define a multi algorithm training. Usage will be based on defer actions, observation space and rewards between its inner algorithms (PPO, DQN, SAC...). It is thought for projects which may rely on different strategies for different actions with a focused training

Example SAC implementation with ReLAx

RL-Odyssey is a research framework for continuous control that implements state-of-the-art RL algorithms (SAC, TD3, PPO, etc.) with clean experiment scripts and interactive notebooks.

Implementation of k-Step Latent (KSL)

Quadruped Ant-v4 Environment Training with Stable-Baselines3