Deep Q-Leaning trained to play Doom (openAI gym env)

Applied reinforcement learning to build a simulated vehicle navigation agent. This project involved modeling a complex control problem in terms of limited available inputs, and designing a scheme to automatically learn an optimal driving strategy based on rewards and penalties.

[INSA-5TC] Artificial Intelligence Project - robot cleaner problem using linear Monte Carlo and Q-Learning

Qar repository

QLearning graphical example

As a means to understanding Q-Learning, a game of noughts and crosses / tic-tac-toe

Research about applying reinforcement learning to realitic problems. Collects data then figure out how good reinforcement learning is.

Automated Car with Reinforcement Learning. Learning is done using penalty and rewards.

Naive Q-Learning approach to self-driving cars

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Barebones Blackjack player with q-learning

Creating agent to make optimized moves to win the game against environment. Using Reinforced Learning running multiple episodes on Q-Learning models

Kaggle live reinforcement learning problem. Make the goose eat the food without bumping into other geese. Based on the mobile phone game .. snake!

Train an agent in a gridworld environment via Q-Learning.

Algorithms and Example Cases for Machine Learning

Dots and Boxes with reinforcement lerning

The project implements a reinforcement learning agent that can play the Space Invaders Atari game. I compare the performance of the agent using Double Deep Q-Learning with simple Deep Q-Learning.

Implement Q-Learning and DQN algorithms to solve FrozenLake problem.

Just another approach to do machine learning stuff on games.