Minecraft reinforcement learning with legacy environment
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Updated
Apr 12, 2024 - Python
Minecraft reinforcement learning with legacy environment
Deep Recurrent Q-Network with different exploration strategies for self-driving cars (using AirSim)
Alogtrader bot using RL
A multi agent reinforcement learning environment where two agents controlled by DRQNs play a custom version of the pursuit-evasion game.
Collision Avoidance with Reinforcement Learning
My DRL(Deep Reinforcement Learning ) algorithm demo, base on pytorch and gym environment.
Deep recurrent Q Learning using Tensorflow, openai/gym and openai/retro
Multi-Agent Deep Recurrent Q-Learning with Bayesian epsilon-greedy on AirSim simulator
This is a reconstruction of previous repository(rl-algorithms).
To keep track and showcase
Implementation of the DQN and DRQN algorithms in Keras and tensorflow
This is the code implementation of the paper "Financial Trading as a Game: A Deep Reinforcement Learning Approach".
DQN-Atari-Agents: Modularized & Parallel PyTorch implementation of several DQN Agents, i.a. DDQN, Dueling DQN, Noisy DQN, C51, Rainbow, and DRQN
Training Deep RL agents in VizDoom.
Master Reinforcement and Deep Reinforcement Learning using OpenAI Gym and TensorFlow
Repository for codes of 'Deep Reinforcement Learning'
Pathfinding Using Reinforcement Learning
Learning to Communicate with Deep Multi-Agent Reinforcement Learning in PyTorch
Implementation of DQN, DDQN and DRQNs for Atari Games in Tensorflow. [Work in Progress]
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