Showing 3 open source projects for "linux mint games"

View related business solutions
  • $300 Free Credits to Build on Google Cloud Icon
    $300 Free Credits to Build on Google Cloud

    New customers can spin up VMs, build with AI, and query data at no cost.

    Put your $300 in credit toward real workloads, then keep building with free monthly usage for 20+ products. No commitment and no charge until you upgrade.
    Start Free
  • Save Up to 91% on Cloud Compute With Spot VMs Icon
    Save Up to 91% on Cloud Compute With Spot VMs

    Automatic sustained-use discounts. One free VM per month. No negotiation needed.

    Run batch jobs at 60-91% off with Spot VMs. Long-running workloads get automatic discounts with sustained use.
    Start Free
  • 1
    Gym

    Gym

    Toolkit for developing and comparing reinforcement learning algorithms

    Gym by OpenAI is a toolkit for developing and comparing reinforcement learning algorithms. It supports teaching agents, everything from walking to playing games like Pong or Pinball. Open source interface to reinforce learning tasks. The gym library provides an easy-to-use suite of reinforcement learning tasks. Gym provides the environment, you provide the algorithm. You can write your agent using your existing numerical computation library, such as TensorFlow or Theano. It makes no...
    Downloads: 2 This Week
    Last Update:
    See Project
  • 2
    Sudoku Maker is a generator for Sudoku number puzzles. It uses a genetic algorithm internally, so it can serve as an introduction to genetic algorithms. The generated Sudokus are usually very hard to solve -- good for getting rid of a Sudoku addiction.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    Coach is a python framework that models the interaction between an agent and an environment in a modular way. With Coach, it is possible to model an agent by combining various building blocks, and training the agent on multiple environments. The available environments allow testing the agent in different fields such as robotics, autonomous driving, games and more. It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next