KNOWLEDGE-BASED SYSTEMS

PI:   João Leite

• The Knowledge-Based Systems Group research goal is to develop more intelligent, autonomous, and accountable software systems. Despite old expectations that computational systems behave intelligently, only more recently have we begun to witness the true potential of Artificial Intelligence, partly because of novel AI techniques, but mostly due to the increase in available data and computational power. However, as AI becomes pervasive, old problems resurface and new challenges arise. This includes ensuring that an AI behaves within certain (e.g. ethical) boundaries; being able to represent knowledge so that an AI can make sense of, reason with, and even share it; and endowing an AI with the ability to explain humans its behaviour. At the heart of these questions lays the need to learn, represent and manipulate knowledge in a way that is formal, efficient, and human understandable, while being exploitable within different kinds of systems.
• Building upon the long-standing tradition of being the first Portuguese group working in AI, the KBS group collaborates with other international and national researchers and practitioners on problems in the broad area of AI, focusing on knowledge representation and reasoning, constraint and optimisation problems, machine learning, and evolutionary game theory. Examples of problems being addressed include developing principled solutions to deal with dynamic heterogeneous knowledge; modelling argumentative debates in social networks; learning to extract explanations from neural-based systems; and developing efficient constraint-based tools.
  
  The KBS group is a national leading research group in AI with an internationally recognized high profile. The group, which includes two ECCAI Fellows, regularly publishes at the top journals such as the AI Journal, ACM TOCL, and TPLP, and top conferences such as IJCAI, AAAI, KR, AAMAS, and ISWC, to whose PCs it regularly belongs.