Using reinforcement learning to train FlappyBird.
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Updated
Dec 4, 2023 - Java
Using reinforcement learning to train FlappyBird.
Implementation of a BDI driver agent that uses BDI plans for high-level path planning and Reinforcement Learning for low-level control. Environment: f1tenth car and simulator.
A platformer where you are aided by clones learning from your behaviour.
Tetris using java and python. Self-learning AI implemented using Pytorch and DQN.
🤖 A web-based game where players build cities and watch DQN and QLearning agents learn to navigate them based on time, weather, and points. Built with React, Java, Python and TensorFlow.js. Perfect for AI enthusiasts curious to try out pre-trained RL algorithms! 🌆👾
A simple RL library, with a focus on DQNs
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