Artificial Intelligence is a discipline whose foundations lie in several scientific fields and involve a variety of different technologies. In this track we consider foundations of AI in a broad perspective, aiming to provide the cornerstones of the scientific activity of the whole center and considering research along three main dimensions:
Basic research, aiming at exploring research avenues which are distinctive of AI. These include traditional topics such as: algorithm selection, computer vision, computational learning theory, computational logic, constraint solving, decision support systems, distributed AI, games, knowledge representation, machine learning, multi-agent systems, natural language processing, robotics, semantic web etc. Moreover, we pay attention to emerging research areas which derive from fruitful interactions between different areas of computer science and AI such as explainable AI, integration of symbolic and sub-symbolic reasoning, differential semantics, programming languages for AI. Architectures and platforms for AI (both hardware and software) are also considered here as they provide the technological ground for efficient and effective implementation of modern AI techniques.
Interdisciplinary research aiming at promoting the cross-fertilisation between AI research and methods and perspective from cognitive sciences and philosophy, bio-engineering and neuroscience, economics, game-theory, logic, sociology, ethics, and law to develop innovative approaches and applications, to be deployed in different domains.
Human-centered AI research aiming at designing AI systems able to interact with humans. Interacting with humans calls for features such as explainability, verifiability, certifiability and ethical and legal standards compliance. Also the impact on society, economy, employment and culture should be carefully considered. Anche l'impatto sulla società, l'economia, l'occupazione e la cultura dovrebbe essere attentamente considerato