PDF] Chrome Dino Run using Reinforcement Learning

This paper has used two of the popular temporal difference approaches namely Deep Q-Learning, and Expected SARSA and also implemented Double DQN model to train the agent and compared the scores with respect to the episodes and convergence of algorithms withrespect to timesteps. Reinforcement Learning is one of the most advanced set of algorithms known to mankind which can compete in games and perform at par or even better than humans. In this paper we study most popular model free reinforcement learning algorithms along with convolutional neural network to train the agent for playing the game of Chrome Dino Run. We have used two of the popular temporal difference approaches namely Deep Q-Learning, and Expected SARSA and also implemented Double DQN model to train the agent and finally compare the scores with respect to the episodes and convergence of algorithms with respect to timesteps.

Google Chrome T-rex Game No Internet Chrome Dino Embroidery

How to Control the Dino Game with Hand Gesture? - Shiksha Online

Using Q learning to play the Chrome Dinosaur game

PDF) Chrome Dino Run using Reinforcement Learning

This AI learned to play Chrome Dino Game

The 7 best deep learning books you should be reading right now

How to play Google Chrome Dino game using reinforcement learning

Google Chrome dinosaur game Python bot.

This AI learned to play Chrome Dino Game

Build an AI to play Dino Run