What if a Tamagotchi had a neural network and could learn stuff?

Dosidicus electronicus

Digital pet squid with a dynamic neural network.

• Part educational neuro tool and part sim game
• Features Hebbian learning, Neurogenesis and a retro aesthetic
• Design your own squid brain with GUI tools and watch it evolve and learn!
• Entirely custom simulation engine - does not use Tensorflow or Pytorch

💿 Compiled binaries for Windows are available on Releases page

user guide and technical stuff can be found on the wiki

Project Overview

Project Name: Dosidicus Description: A Tamagotchi-style digital pet simulator with an integrated neural network brain. The pet learns, adapts, and requires user interaction for care, feeding, and training. Features customizable neural networks for diverse behaviors and personalities.

• Dependencies:
  • Python ^3.9
  • PyQt5 ^5.15 (GUI framework)
  • numpy ^1.21 (neural network computations)
• Core Structure: Modular codebase in src/ including brain designer, decision engine, learning algorithms, personality traits, memory management, UI components, and interaction systems. Entry point via main.py.

Key Project Components

• Plugin System: Extensible architecture with built-in plugins for achievements (tracking milestones) and multiplayer (networked interactions).
• Save System: Persistent saves in saves/ for pet states, autosaves, and achievement logs.
• Headless Mode: Standalone training and simulation in headless/ for GUI-less operation, ideal for background training or server environments.
• Custom Brains: Library of pre-configured neural networks in custom_brains/ (e.g., "Plant-Seeker", "Grasshopper") for quick behavior setup.
• Memory Management: Dual memory system (_memory/) with long-term and short-term storage for learning persistence.
• Examples and Tools: Example squids, configuration files (config.ini), and version tracking.

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Thank you for your interest in my project! Please fork and contribute!