Education & Research Portal – Blob IQ
Bridging Gaming, Research, and Learning
Blob IQ is a real-time neural experimentation platform positioned at the intersection of three fields: video game technology, applied artificial intelligence, and scientific education.
Each entity (Blob) contains a dynamic neural network capable of perceiving, learning, dreaming, and evolving over generations. Designed as a living simulation, Blob IQ opens new frontiers for exploring artificial cognition in visual, interactive, and modular environments.
Why use Blob IQ in education?
Let students observe a neural network learning in real time
Make complex concepts tangible: LSTM, backpropagation, NEAT
Go beyond theory by manipulating a living, evolving system
Introduce ethics, neuroevolution, and architecture of synthetic intelligences
Educational & Scientific Objectives
Teach how a real neural network works inside a 3D engine
Demonstrate perception, supervised learning, LSTM memory, and gradient descent
Provide an interactive playground for labs, workshops, and experimental AI modules
Analyze behavioral evolution through controlled neuroevolution and mutation
Scientific Foundations of the Neural Engine
Multilayer adaptive neural network with LSTM
Supervised and reinforcement learning mechanisms
NEAT-inspired architecture for evolving topologies
Memory consolidation via Experience Replay
Neural dreaming through dream replay simulation
Every Blob decision stems from autonomous neural computation, with no pre-scripted logic or behavior trees.
Technical Architecture
Engine: Unity 6 + C# / Burst Compiler / DOTS
Neural design: multilayer + LSTM (random init + evolutionary mutation)
Full parallelization of AI modules: prediction, feedback, learning loop
Exposed data: activations, gradients, weights, training history
Use Cases in Educational Settings
Track behavioral evolution of a Blob over multiple generations
Observe the impact of supervised learning on task performance
Compare topologies and analyze decision-making strategies
Dynamically modify mutation rates, rewards, or energy costs
Design a mini experimental protocol around a behavioral goal
Included Resources:
Downloadable scientific brief (.PDF)
Access to neural logs & saved weights
Built-in neural network visualizer (structure + live activations)
Key Scientific References
LSTM – Understanding LSTM Networks
NEAT – Stanley et al., 2002
Dream Replay – arXiv:2006.03761
Human-in-the-loop – arXiv:1704.03732
Academic Partnerships & Integration
Are you looking to:
Integrate Blob IQ into a university course or research program?
Use it as a scientific outreach tool in conferences or exhibitions?
Run an experimental study or demonstrate learning systems in action?
📩 Contact us directly via dfgamesstudio.com/en/blob-iq or the YouTube channel @FormationUE5Unity for personalized support.
Blob IQ is a platform built for exploration, pedagogy, and cognitive innovation.