What is needed so that robots can work along humans? The AI-powered systems will need to communicate with people and follow external regulations so that they can be gracefully and safely incorporated into the society. Contemporary Artificial Intelligence (AI) systems have no way to directly incorporate any of the rules known to humans.

I would like to address the challenge of rules extraction from, and injection into, neural networks by creating the adaptable Neural-Symbolic integration appropriate for the application in Industry 4.0 and robotics.

What is GARRET?

The Generative AdveRsarial Rules ExTractor (GARRET) is inspired by the capabilities of the Generative Adversarial Networks (GANs) and Reinforcement Learning (RL).

The system could find its direct application in Risk Assessment and Predictive Maintenance fields and can be considered a stepping stone for Neural-Symbolic integration introduction to robotics.

About Me

My name is Maciej Wielgosz, and I’m a Cognitive Computing researcher, with an emphasis on real-time anomaly detection. In 2010, I received the Ph.D. degree in High-Performance Reconfigurable Computing from the AGH University of Science and Technology in Krakow, Poland. Now I’m an assistant professor in the Department of Electronics there and also work in the Academic Computing Centre CYFRONET.