Self Play Actor Critic, Reinforcement Learning on TROY; all puns intended
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Updated
Oct 3, 2023 - Python
Self Play Actor Critic, Reinforcement Learning on TROY; all puns intended
Remember the sad Marvin from "Hitchhiker's guide to the galaxy"? In this project we train him to walk from the scratch using only pure python with numpy!
Exploring the fundamentals of neural networks
Policy Gradients, DDPG, and TD3 in gym env
Vanilla Policy Gradient (REINFORCE) implementation with PyTorch
Udacity Deep Reinforcement Learning Nanodegree. Second Project Implementation (Continuous Control).
Implementations of Rl algorithms ranging from Q-learning to Multi-Agent RL using DDPG in unity and gym environments.
The objective of this project is to develop an autonomous agent to perform well in the first person shooting games using various reinforcement learning techniques.
Project 2 of Udacity Deep Reinforcement Learning Nanodegree
Solutions to the Stanford CS:234 Reinforcement Learning 2022 course assignments.
Projects for The School of AI
Code for an intro to RL workshop. You'll be training a simple agent to play pong using policy gradients. Adapted from http://karpathy.github.io/2016/05/31/rl/
ReLAx - Reinforcement Learning Applications Library
Model-based Policy Gradients
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
A Universal Deep Reinforcement Learning Framework
Basic reinforcement learning algorithms. Including:DQN,Double DQN, Dueling DQN, SARSA, REINFORCE, baseline-REINFORCE, Actor-Critic,DDPG,DDPG for discrete action space, A2C, A3C, TD3, SAC, TRPO
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
Implementations of Deep Reinforcement Learning Algorithms and Bench-marking with PyTorch
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
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