Showing 6 open source projects for "reinforcement learning"

View related business solutions
  • Try Google Cloud Risk-Free With $300 in Credit Icon
    Try Google Cloud Risk-Free With $300 in Credit

    No hidden charges. No surprise bills. Cancel anytime.

    Use your credit across every product. Compute, storage, AI, analytics. When it runs out, 20+ products stay free. You only pay when you choose to.
    Start Free
  • Gemini 3 and 200+ AI Models on One Platform Icon
    Gemini 3 and 200+ AI Models on One Platform

    Access Google's best plus Claude, Llama, and Gemma. Fine-tune and deploy from one console.

    Build generative AI apps with Vertex AI. Switch between models without switching platforms.
    Start Free
  • 1
    MCiSEE

    MCiSEE

    All of Minecraft, EASILY get Minecraft resources

    MCiSEE is an open-source project designed to integrate Minecraft with computer vision and artificial intelligence experiments. The system focuses on capturing visual information from the game environment and exposing it to external programs for analysis or machine learning research. By converting gameplay data into visual or structured formats, MCiSEE enables researchers and developers to build AI agents capable of interacting with the Minecraft environment. The project can be used as a research platform for tasks such as reinforcement learning, perception analysis, or automated gameplay strategies. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • 2
    neurojs

    neurojs

    A JavaScript deep learning and reinforcement learning library

    neurojs is a JavaScript framework designed to enable deep learning and reinforcement learning directly within web environments. The library provides a full machine learning framework implemented in JavaScript that can run inside browsers or Node.js environments. It focuses particularly on reinforcement learning algorithms, enabling developers to create intelligent agents that learn through interaction with simulated environments.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    Pwnagotchi

    Pwnagotchi

    Deep Reinforcement learning instrumenting bettercap for WiFi pwning

    ...This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario or Atari games like most reinforcement learning based “AI” (yawn), Pwnagotchi tunes its own parameters over time to get better at pwning WiFi things in the real world environments you expose it to. To give hackers an excuse to learn about reinforcement learning and WiFi networking, and have a reason to get out for more walks.
    Downloads: 4 This Week
    Last Update:
    See Project
  • 4
    Supervised Reptile

    Supervised Reptile

    Code for the paper "On First-Order Meta-Learning Algorithms"

    The supervised-reptile repository contains code associated with the paper “On First-Order Meta-Learning Algorithms”, which introduces Reptile, a meta-learning algorithm for learning model parameter initializations that adapt quickly to new tasks. The implementation here is aimed at supervised few-shot learning settings (e.g. Omniglot, Mini-ImageNet), not reinforcement learning, and includes scripts to run training and evaluation for few-shot classification. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Our Free Plans just got better! | Auth0 Icon
    Our Free Plans just got better! | Auth0

    With up to 25k MAUs and unlimited Okta connections, our Free Plan lets you focus on what you do best—building great apps.

    You asked, we delivered! Auth0 is excited to expand our Free and Paid plans to include more options so you can focus on building, deploying, and scaling applications without having to worry about your security. Auth0 now, thank yourself later.
    Try free now
  • 5
    DeepTraffic

    DeepTraffic

    DeepTraffic is a deep reinforcement learning competition

    ...The project was created as part of an educational competition associated with MIT’s deep learning courses, encouraging students and researchers to experiment with reinforcement learning techniques. The environment provides a coding interface where users can design neural network architectures and tune hyperparameters while observing their agent’s performance in a visual simulation.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 6
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ConvNetJS is a Javascript library for training Deep Learning models (Neural Networks) entirely in your browser. Open a tab and you're training. No software requirements, no compilers, no installations, no GPUs, no sweat. ConvNetJS is an implementation of Neural networks, together with nice browser-based demos. It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. ...
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
MongoDB Logo MongoDB