Environnement Gym de flappy Bird
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Updated
Aug 2, 2019 - Python
Environnement Gym de flappy Bird
Research internship during the 5th semester of my B.Sc CBT degree @ TUM CS
This repository provides implementations of a Q-learning agent to balance a pole on a cart.
This repository is intended for developing reinforcement learning algorithms.
An RL environment and a Monte Carlo evaluation framework for Basel disclosure optimization
Gym Armed Bandits is an environment bundle for OpenAI Gym
The gym-cityflow environment is a multiagent domain featuring large discrete state and action spaces. An environment can be created from any set of cityflow config files
Compare q-learning, SARSA and Expected SARSA to solve AI gym's Taxi-v3 environment
Chess AI bot using the minimax algorithm, building upon gym-chess. Used Stockfish for the Evaluation Function
Gym environments for logistics tasks that can be described as "Move something from A to B"
C++ implementation of the continuous LunarLander environment.
Custom reinforcement learning implementations
Simulating the Blackjack card game using Monte Carlo methods
Genetic Algorithm as a tool for optimising neural networks
The game of Yaniv implemented as a Gymnasium environment to be used for Reinforcement Learning.
🚀 A simple and intuitive BMI Calculator web application for quick health assessments. Enter your weight and height, get instant results, and understand your BMI. Built with HTML, CSS, and JavaScript.
Creating Gym Website for using html css and js.
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