2048 environment for Reinforcement Learning and DQN algorithm
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Updated
May 27, 2022 - Python
2048 environment for Reinforcement Learning and DQN algorithm
基于DQN算法的投球2D仿真,没有考虑空气阻力,仅用于算法理解
A Streamlit application demonstrating Reinforcement Learning (RL) for intelligent product recommendations in online advertising. Explore different RL algorithms and their impact on personalization.
First I created an environment of openAI and Gymnasium I have campared Q-Learning Algoirthm and and DQN Learning Algorithm I got best reward DQN Because It's advance
The "Reinforcement Learning Snake Game" project uses Deep Q-Learning to train an AI agent to play Snake autonomously. The agent learns to maximize its score by eating apples and avoiding collisions, demonstrating reinforcement learning in a game environment. The project includes game logic, RL agent code, and training scripts.
Implementations of some of the most well known Deep Reinforcement Learning algorithms
A small demo of RL algorithms on a trash collector robot
Reinforcement Learning: Cartpole Balancing with a DQN Agent
# FreeHoopRLThis project uses a Deep Q-Network (DQN) algorithm to train an AI agent for shooting basketballs in a simple 2D environment. The agent learns to choose the right angle and force to score points, with results visualized through training and analysis graphs. 🎉🤖
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