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.
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)
Tests SOTA algorithms using pendulum as baseline environment
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Example SAC implementation with ReLAx
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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
Soft Actor Critic Agent implementation in Python
A project in reinforcement learning done for a collage course. Two RL algorithms will be compared - Soft actor critic (policy optimization) and Deep Q Network (Q-Learning).
Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
[Reinforcement Learning, forked from Stable-baselines3] Étude des performances des algorithmes de Reinforcement Learning sur Pendulum
Reinforcement Learning and Deeep reinforcement Learning
Playing around with RL (mostly stand-alone RL methods)
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