Main research interests focus on knowledge representation and reasoning, with an emphasis on Answer Set Programming (ASP) and normative multi-agent systems.
ASP is a declarative programming paradigm using AnsProlog, allowing intuitive problem and solution constraint descriptions rather than algorithmic implementations.
Normative multi-agent systems regulate behavior in open distributed systems through social-like norms.
Interested in the theory, implementation, and applications of ASP and normative systems, with past applications in structural engineering, music composition, legal reasoning, business rules, and policy modeling.
Also interested in inductive machine learning, explainable and verifiable AI, hybrid AI (combining knowledge-driven and data-driven techniques), legal reasoning, argumentation, and game theory.
Willing to supervise doctoral students in declarative programming, ASP (theory/methodology/application), explainable AI, hybrid AI, normative multi-agent systems (norm emergence, change, applications), policy modeling, and legal reasoning.