În cadrul Seminarului de Inovare și Dezvoltare din cadrul Departamentului de Informatică, Dr. Sebastian Rudolph, profesor în cadrul Computational Logic at the Institute for Artificial Intelligence at the Faculty of Computer Science at the Technische Universität Dresden, va susține în data de 8.06.2022 o prelegere intitulată The More the Worst-Case-Merrier: A Generalized Condorcet Jury Theorem for Belief Fusion.

Evenimentul se va desfășura online începând cu ora 11.10 pe platforma Microsoft Teams, la această adresă.

Abstract: In multi-agent belief fusion, there is increasing interest in results and methods from social choice theory. As a theoretical cornerstone, the Condorcet Jury Theorem (CJT) states that given a number of equally competent, independent agents where each is more likely to guess the true out of two alternatives, the chances of determining this objective truth by majority voting increase with the number of participating agents, approaching certainty. Past generalizations of the CJT have shown that some of its underlying assumptions can be weakened. Motivated by requirements from practical belief fusion scenarios, we provide a significant further generalization that subsumes several of the previous ones. Our considered setting simultaneously allows for heterogeneous competence levels across the agents (even tolerating entirely incompetent or even malicious voters), and voting for any number of alternatives from a finite set. We derive practical lower bounds for the numbers of agents needed to give probabilistic guarantees for determining the true state through approval voting. We also demonstrate that the non-asymptotic part of the CJT fails in our setting for arbitrarily high numbers of voters.

Sebastian Rudolph is a full professor for Computational Logic at the Institute for Artificial Intelligence at the Faculty of Computer Science at the Technische Universität Dresden, since 2021 affiliated member of the Faculty of Mathematics. His research interests comprise Artificial Intelligence, in particular Knowledge Representation and Reasoning using diverse formalisms (such as Description Logics, Existential Rules and Formal Concept Analysis) and their applications in diverse areas, for instance Semantic Technologies. He deals with problems ranging from theoretical foundations (e.g., decidability and complexity of reasoning tasks) to practical deployment (ontology modeling, interactive knowledge acquisition). In 2017, prof. Sebastian Rudolph received an ERC Consolidator Grant for investigating general principles of decidability in logic-based knowledge representation.