mario-ai

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mario-ai is an open-source Python framework that leverages NeuroEvolution of Augmenting Topologies (NEAT) to evolve neural network-based AI agents capable of playing Super Mario Bros. It integrates with OpenAI Gym’s SuperMario environment, providing customizable fitness functions, real-time training visualization, genome saving/loading, and performance monitoring. Users can adjust mutation parameters, define evaluation metrics, and visualize learned network topologies.
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May 07 2025
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mario-ai

mario-ai

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0
mario-ai
mario-ai is an open-source Python framework that leverages NeuroEvolution of Augmenting Topologies (NEAT) to evolve neural network-based AI agents capable of playing Super Mario Bros. It integrates with OpenAI Gym’s SuperMario environment, providing customizable fitness functions, real-time training visualization, genome saving/loading, and performance monitoring. Users can adjust mutation parameters, define evaluation metrics, and visualize learned network topologies.
Added on:
Social & Email:
Platform:
May 07 2025
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What is mario-ai?

The mario-ai project offers a comprehensive pipeline for developing AI agents to master Super Mario Bros. using neuroevolution. By integrating a Python-based NEAT implementation with the OpenAI Gym SuperMario environment, it allows users to define custom fitness criteria, mutation rates, and network topologies. During training, the framework evaluates generations of neural networks, selects high-performing genomes, and provides real-time visualization of both gameplay and network evolution. Additionally, it supports saving and loading trained models, exporting champion genomes, and generating detailed performance logs. Researchers, educators, and hobbyists can extend the codebase to other game environments, experiment with evolutionary strategies, and benchmark AI learning progress across different levels.

Who will use mario-ai?

  • AI researchers
  • Game AI hobbyists
  • Educational instructors
  • Students in AI
  • Evolutionary algorithm enthusiasts

How to use the mario-ai?

  • Step1: Clone the mario-ai repository from GitHub.
  • Step2: Install dependencies with pip install -r requirements.txt and gym-super-mario-bros.
  • Step3: Configure the NEAT parameters in config-feedforward.txt to adjust fitness and mutation settings.
  • Step4: Run the training script (python train.py) to start evolving AI agents.
  • Step5: Monitor training metrics and visualize neural networks via provided scripts.
  • Step6: Once satisfied, save the best genome and use python play.py to watch the AI play.

Platform

  • mac
  • windows
  • linux

mario-ai's Core Features & Benefits

The Core Features

  • Neuroevolution via NEAT
  • OpenAI Gym SuperMario integration
  • Customizable fitness functions
  • Real-time training visualization
  • Save/load genome models
  • Performance logging and export

The Benefits

  • Automated game playing AI
  • Highly customizable evolution parameters
  • Educational tool for neuroevolution
  • Open-source and extensible
  • Easy model evaluation and visualization

mario-ai's Main Use Cases & Applications

  • Educational demos on neuroevolution
  • Research in evolutionary game AI
  • Benchmarking AI performance
  • Creating game-playing bots for entertainment
  • Experimenting with custom fitness functions

FAQs of mario-ai

mario-ai Company Information

mario-ai Reviews

5/5
Do You Recommend mario-ai? Leave a Comment Below!

mario-ai's Main Competitors and alternatives?

  • marI/O by SethBling
  • NEAT-Python
  • OpenAI Gym Retro

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