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Feb 13, 2020 · In this tutorial we are going to recreate a game of Breakout using Python and the Pygame library. The Pygame library is the perfect library to build basic 2D arcade games and to start developing your OOP skills.
Apr 17, 2023 · In this blog post, we’ll explore how to use reinforcement learning to train an AI agent to play the classic Atari game, Breakout. We’ll discuss the Deep Q-Network (DQN) algorithm, which is a popular technique for training game-playing AI agents.
May 28, 2018 · The original deep RL methods that were used to play Atari games came from Mnih et al., Playing Atari with Deep Reinforcement Learning (and the more cited Nature paper), where Mnih and colleagues used the model-free reinforcement learning algorithm Q-learning, paired with a deep neural network to approximate the action-value Q-function, to play ...
- Setting Up A Python Environment
- Training An Agent
- Wrapup
For starters I highly recommend installing Anaconda from https://www.anaconda.com for managing your Python environments. Anaconda allows you to run multiple versions of Python in parallel with specific versions of required packages that you can bundle in an environment. Anaconda is available for Linux, Windows and Mac. Regarding OS choice I only ha...
I will be training an agent to learn to play Space Invaders for this example. Globally there are two approaches to learning Atari games: 1. Learn from the game state as it is represented on screen. The Atari 2600 boasts a resolution of 160x192 pixels on 3 color channels making total of 92160 input variables. 2. Learning the game state from its inte...
I have shown you two approaches of getting started with training your own agent for playing the Atari 2600 game of Space Invaders using a deep reinforcement learning technique using Keras-RL2, both by using the console video output and its internal game state from RAM. At this point I have found more suitable approaches for beginners which allow yo...
Jul 8, 2021 · In this post, I will be further exploring Deep Q learning but in the context of Atari games. In 2013, the paper by the Deepmind team Playing Atari with Deep Reinforcement Learning (Mnih et. al)...
Feb 15, 2019 · Reinforcement learning algorithms have defeated world champions in complex games such as Go, Atari games, and Dota 2. I wanted to see how this works for myself, so I used a DQN as described in Deepmind’s paper to create an agent which plays Breakout.
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Research Playground built on top of OpenAI's Atari Gym, prepared for implementing various Reinforcement Learning algorithms. It can emulate any of the following games: Check out corresponding Medium article: Atari - Reinforcement Learning in depth 🤖 (Part 1: DDQN)
