A multi-disciplinary team, which includes computer scientists, engineers, psychologists, and lawyers, conducts both theoretical and experimental research related to Reinforcement Learning, Learning by Demonstration, and Computational Cognition.

The focus of our research is on Reinforcement Learning and the main research topics are safe reinforcement learning, multi-agent reinforcement learning, hierarchical reinforcement learning, learning by demonstrations and imitation learning, transfer learning, cognitive architectures, explainable AI, ethical AI, and AI legal framework compliance.

Application fields include Healthcare&Well Being, Business&Finance, Resource Management, Manufacturing, Robotics, and Telecommunications.

The Laboratory is organized into the following Research Units:

• • AI Theories, methods, and algorithms
  • AI Legal framework, Explainable AI, and Ethical AI
  • AI4Healthcare&Well Being
  • AI4Manufacturing, Resource Management, and Business&Finance
  • AI4Robotics and Telecommunications