AI for Cognitive Cyber-Physicial Systems interoperability

AI4C2PS focuses on setting continuous interoperability to collaborative enterprises systems composed of Cyber-Physical Systems (CPS) and Humans, working together for a common objective.

Exploiting the Digital Twin (DT) concept in a decentralised way where each CPS and Human is twinned, AI4C2PS seeks to bridge Knowledge Representation and Reasoning with Deep Reinforcement Learning (DRL) techniques to maintain semantic interoperability within the resulting system-of-systems.

This is obtained by building an emulation environment where DTs embed semantic reasoning, DRL and explainable AI capabilities to learn from the interactions between entities. DTs continuously enrich their knowledge base from simulations and from actual interoperations at runtime, with semantically enhanced axioms extracted from the learning process.

The goal is to form cognitive CPS from the couples <CPS, DT>, able to interoperate with other CPS and humans in a seamless way whatever happens during their interactions.