Comparing different algorithm performances on Atari games such as Pong
-
Updated
Feb 17, 2021 - Python
Comparing different algorithm performances on Atari games such as Pong
Deep Q-learning with TensorFlow
Replicating DeepMind experiments on Atari Games using Deep RL
In this project, we attempt to equip the agent with the recognition of basic components of an Atari game environment through curriculum learning—gleaned from human developmental psychology—and evaluate its performance. Our best agent was pre-trained on a carefully designed curriculum to learn to complete a new game 5x faster than regular agents.…
Code associated with the paper "Ego Networks"
It is a project of exploring reinforcement-learning on Atari-Freeway game.
Remake of the Atari classic "Missile Command"
I'm an AI, I play Atari's breakout in my spare time.
Implementation of popular RL algorithms for Atari games
This is a clone with some personal features of old Breakout game written in Python with PyGame module.
This code implements an Asynchronous Advantage Actor-Critic (A3C) algorithm using PyTorch to train an agent to play the Atari game "Boxing"
Atari Breakout clone written in Python.
Reinforcement learning algorithm to beat Atari games. Based on OpenAI's gym library.
2022 Spring Semester, Personal Project Research
A colorful spin on Atari's game of Missile Command.
Implementation of DQN, DDQN and DRQNs for Atari Games in Tensorflow. [Work in Progress]
⛷ DQN and DDQN algorithms for OpenAI Gym Skiing environment 🎮
Add a description, image, and links to the atari-games topic page so that developers can more easily learn about it.
To associate your repository with the atari-games topic, visit your repo's landing page and select "manage topics."