Automated Planning

Coordinator: Alfonso Gerevini

Automated Planning is one of the cornerstone fields of Artificial Intelligence, being actively studied since the '60s.

The purpose of automated planning research is to develop formally well-founded and domain-independent techniques and methods to design agents that can pursue their goal while interacting with their environment.

The domain-independence of these techniques is the main advantage — and the main source of hardness — of AI planning, whose methods can be employed and adapted to a great variety of domains, in contrast to the development of ad-hoc algorithmic techniques for the specific problem at hand.

In this thematic area, great emphasis is given to the formal foundations of planning techniques, which have to guarantee to find a correct strategy to pursue the given goal, making AI planning a central component of any trustworthy AI infrastructure.

Formal Methods

Coordinator: Adriano Peron

The development of complex system deployed in business-critical or safety-critical scenarios need to be approached with care as to avoid irreparable incidents.

For this reason, many techniques have been devised in the last decades to help ensuring the highest possible levels of safety and trust in the development of such systems.

The Formal Methods field encompass a great variety of methods, tools, and techniques to model complex systems, studying their behavior, check their correctness with respect to formal specifications, or synthesize correct-by-construction implementations base on such specifications.

In this thematic area, particular attention is devoted to the application of such techniques to artificial intelligence systems, that by the nature of their applications most require safety assurance.

Discrete and continuous hybrid systems

Coordinator: Tiziano Villa

Complex systems, including those driven by artificial intelligence technologies, do not often operate in isolation but interact with the physical world. When the interaction with the environment involves continuous physical phenomena, the formal tools and techniques used to model, verify, and synthesise such systems change drastically, entering the realm of Cyber-Physical Systems (CPSs).

By their nature, CPSs are often employed in safety-critical scenarios. It is thus crucial to study how such system can be modeled and verified.

In this thematic area, Cyber-Physical Systems are studied in their connection with complex systems guided by artificial intelligence, to study and develop techniques ensure their safety and trustability.