A digital pet with a simple neural network [research project]

• Includes tools for visualising and understanding neural networks, Hebbian learning and Neurogenesis
• requires PyQt5 and numpy

Autonomous Behavior:

• The squid neural network makes autonomous decisions based on current state (hunger, sleepiness, etc.).
• Implements a vision cone for food detection, simulating realistic foraging behavior.
• Hebbian learning algorithm runs every 30 seconds (configurable)
• Experiences from short-term and long-term memory can influence decision-making
• Squid can create new neurons in response to his environment (Neurogenesis)