Simple pytorch implementations of RL algorithms
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Updated
Jul 7, 2022 - Python
Simple pytorch implementations of RL algorithms
Labs for the Robot Learning class, focusing on robotics and Reinforcement Learning. Each lab focuses on a different topic, had mandatory tasks and eventually extensions. All the results have been discussed in the reports.
Autonomous Driving W/ Deep Reinforcement Learning in Lane Keeping - DDQN and SAC with kinematics/birdview-images
Pytorch Implementation of TD3 and SAC algorithms on Mujuco Models
Documentation and implementation of a Reinforcement Learning approach designed to automate inverse kinematics for manipulation tasks involving the arms of SoftBank Robotics' Pepper robot.
⌨️ The SaC programming language IDE submodule for SNU Programming Tools (2D Mode)
A general deep reinforcement learning frames for atari games by pytorch.
Pytorch Implementation of Soft Actor Critic (SAC)
Funções de Sistemas de Financiamento comparação Gráfica - SAC, PRICE, SAA - Matplotlib
Bipedal Walker agent trained using SAC model on OpenAI Gym Environment.
🚤🏖️BOATS DO VZHHHHH BBBDROOM, BEEEEP, BEEEP, GNAA, HONK, VZHHHHHHHHHHHHHH🏖️🚤
Re-implementation of Soft-Actor-Critic (SAC) in TensorFlow 2.0
Jaxplorer is a Jax reinforcement learning (RL) framework for exploring new ideas.
Custom Reinforcement Learning Agents
Explainability of Deep RL algorithms using graph networks and layer-wise relevance propagation.
Soft Actor-Critic (SAC) algorithm implementation on Robosuite Panda robot (Pytorch)
Reinforcement Learning with Robot Arm
Yet another deep reinforcement learning
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
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