Popular GitHub Repositories for Lstmppo Drl Stocktrader

FinRL: Financial Reinforcement Learning. ?

An elegant PyTorch deep reinforcement learning library.

Massively Parallel Deep Reinforcement Learning. ?

OpenDILab Decision AI Engine. The Most Comprehensive Reinforcement Learning Framework B.P.

Clean, Robust, and Unified PyTorch implementation of popular Deep Reinforcement Learning (DRL) algorithms (Q-learning, Duel DDQN, PER, C51, Noisy DQN, PPO, DDPG, TD3, SAC, ASL)

PPO x Family DRL Tutorial Course（决策智能入门级公开课：8节课帮你盘清算法理论，理顺代码逻辑，玩转决策AI应用实践 ）

Concise pytorch implements of DRL algorithms, including REINFORCE, A2C, DQN, PPO(discrete and continuous), DDPG, TD3, SAC.

PyTorch implementations of various Deep Reinforcement Learning (DRL) algorithms for both single agent and multi-agent.

Code implementation of "Learning Efficient Online 3D Bin Packing on Packing Configuration Trees". We propose to enhance the practical applicability of online 3D Bin Packing Problem (BPP) via learning on a hierarchical packing configuration tree which makes the deep reinforcement learning (DRL) model easy to deal with practical constraints and well-performing even with continuous solution space.

gym-gazebo2 is a toolkit for developing and comparing reinforcement learning algorithms using ROS 2 and Gazebo

AutoPentest-DRL: Automated Penetration Testing Using Deep Reinforcement Learning

Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch

Deep Reinforcement Learning (DQN) based Self Driving Car Control with Vehicle Simulator

Code of Paper "Joint Task Offloading and Resource Optimization in NOMA-based Vehicular Edge Computing: A Game-Theoretic DRL Approach", JSA 2022.

Courses on Deep Reinforcement Learning (DRL) and DRL papers for recommender systems

A deep reinforcement learning (DRL) based approach for spatial layout of land use and roads in urban communities. (Nature Computational Science)

[T-RO 2023] DRL-VO: Learning to Navigate Through Crowded Dynamic Scenes Using Velocity Obstacles

A QoE-Oriented Computation Offloading Algorithm based on Deep Reinforcement Learning (DRL) for Mobile Edge Computing (MEC) | This algorithm captures the dynamics of the MEC environment by integrating the Dueling Double Deep Q-Network (D3QN) model with Long Short-Term Memory (LSTM) networks.

A pytorch tutorial for DRL(Deep Reinforcement Learning)

Curated list for Deep Reinforcement Learning (DRL): software frameworks, models, datasets, gyms, baselines...