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  • MLPro - Elevate your machine learning journey

Welcome to MLPro

  • 1. Introduction
  • 2. Getting started

Basic Functions

  • 3. MLPro-BF - Basic Functions

Machine Learning

  • 4. MLPro-SL - Supervised Learning
  • 5. MLPro-OA - Online Adaptivity
  • 6. MLPro-RL - Reinforcement Learning
  • 7. MLPro-GT - Game Theory

Extension Hub

  • 8. General information
  • 9. Third-party extensions

Appendices

  • A1 - Example pool
  • A2 - API reference
    • MLPro-BF - Basic Functions
    • MLPro-SL - Supervised Learning
    • MLPro-OA - Online Adaptivity
    • MLPro-RL - Reinforcement Learning
    • MLPro-GT - Game Theory
      • MLPro-GT-DynamicGames - Dynamic games
      • MLPro-GT-Native - Native game theory
      • Pool objects
        • Dynamic Games
        • Native GT
    • 3rd Party Support
  • A3 - Project MLPro
MLPro Documentations
  • A2 - API reference
  • MLPro-GT - Game Theory
  • Pool objects
  • Edit on GitHub

Pool objects

  • Dynamic Games
    • Game Boards
      • Bulk Goods Plant
      • Multi-Cartpole
    • Policies
      • State-based Potential Games
  • Native GT
    • Games
      • 2P Prisoners Dilemma
      • 3P Prisoners Dilemma
      • Rock, Paper, Scissors
      • 3P Routing Problems
      • 3P Supply and Demand
    • Solvers
      • Greedy Policy
      • Random Solver
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