PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
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Updated
Mar 24, 2023 - Python
PyTorch implementation of DQN, AC, ACER, A2C, A3C, PG, DDPG, TRPO, PPO, SAC, TD3 and ....
Code for paper "Computation Offloading Optimization for UAV-assisted Mobile Edge Computing: A Deep Deterministic Policy Gradient Approach"
A Pytorch implementation of the multi agent deep deterministic policy gradients (MADDPG) algorithm
PyTorch implementation of Soft-Actor-Critic and Prioritized Experience Replay (PER) + Emphasizing Recent Experience (ERE) + Munchausen RL + D2RL and parallel Environments.
Solutions of assignments of Deep Reinforcement Learning course presented by the University of California, Berkeley (CS285) in Pytorch framework
A Universal Deep Reinforcement Learning Framework
强化学习算法库,包含了目前主流的强化学习算法(Value based and Policy based)的代码,代码都经过调试并可以运行
A trading bitcoin agent was created with deep reinforcement learning implementations.
PyTorch implementation of D4PG with the SOTA IQN Critic instead of C51. Implementation includes also the extensions Munchausen RL and D2RL which can be added to D4PG to improve its performance.
Chapter notes and exercise solutions for Reinforcement Learning: An Introduction by Sutton and Barto
Implemenation of DDPG with numpy only (without Tensorflow)
Solving CartPole-v1 environment in Keras with Actor Critic algorithm an Deep Reinforcement Learning algorithm
PyTorch Implementation of Soft Actor-Critic Algorithm
Implementation of Reinforcement Algorithms from scratch
Project Solutions for my Deep Reinforcement Learning Nanodegree at Udacity
A novel method to incorporate existing policy (Rule-based control) with Reinforcement Learning.
Reinforcement learning, Policy Gradient, Actor-Critic, AC, Agent-based Simulation, Simple-world
This Repository contains my projects!
Implementation of the DDPG algorithm to solve Continuous Control Reacher Environment
Reinforcement Learning - PPO (Proximal Policy Optimization) Implementation to Pong Game
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