Project 2 of Udacity Deep Reinforcement Learning Nanodegree
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Updated
Jan 17, 2019 - Jupyter Notebook
Project 2 of Udacity Deep Reinforcement Learning Nanodegree
Implementation of Algorithms from the Policy Gradient Family. Currently includes: A2C, A3C, DDPG, TD3, SAC
A collection of several Deep Reinforcement Learning techniques (Deep Q Learning, Policy Gradients, ...), gets updated over time.
Exploring the fundamentals of neural networks
Implementations of Deep Reinforcement Learning Algorithms and Bench-marking with PyTorch
Model-based Policy Gradients
Learn Deep Reinforcement Learning in 60 days! Lectures & Code in Python. Reinforcement Learning + Deep Learning
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.
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
Implementations of Rl algorithms ranging from Q-learning to Multi-Agent RL using DDPG in unity and gym environments.
Udacity Deep Reinforcement Learning Nanodegree. Second Project Implementation (Continuous Control).
Policy Gradients, DDPG, and TD3 in gym env
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
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!
Solutions to the Stanford CS:234 Reinforcement Learning 2022 course assignments.
A Universal Deep Reinforcement Learning Framework
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/
Vanilla Policy Gradient (REINFORCE) implementation with PyTorch
ReLAx - Reinforcement Learning Applications Library
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