Research Units

Research at the Institute for Logic, Language and Computation is organized into six research units. Below are short descriptions of these programs.

Mathematical and Computational Logic (MCL)

The unit focuses on gaining a deeper understanding of the nature of information and the processes of reasoning and computation. Researchers in the unit are internationally recognised as leading figures on foundational issues in mathematics, theoretical computer science and AI. Foremost, the unit builds on astrong tradition of research in logic in the Netherlands going back to Brouwer, Heyting and Beth. While being best known for our work in intuitionistic and modal logic, we cover most of the classical areas of mathematical logic such as set theory, computability theory, category theory, proof theory and algebraic logic. In theoretical computer science, the unit is famous for its work on coalgebraic and fixed point logics, as well as type theory and the computational content of proofs. In AI, we contribute to the fields of multi-agent systems and formal learning theory. Through its foundational work the unit contributes to neighbouring topics ranging from formal epistemology, decision theory, game theory to cognitive science. [Go to overview of people affiliated to this Unit]

Formal Semantics and Philosophical Logic (FSPL)

The research focus of this unit is the study, through the application of formal tools, of information transfer and communication through meaningful language use, as well as of key philosophical problems. The unit brings together researchers who are a leading force within formal semantics and pragmatics and within philosophical logic.

Researchers in this unit investigate linguistic phenomena such as epistemic modals, conditionals, indexicals, quantifiers, free choice, rejection and questions as well as philosophical concepts such as vagueness, truth, consequence and conceivability.

A distinctive feature of the unit is the plurality of methods used to pursue the research objectives. Members of the unit draw on a variety of logical tools (different logics such as modal, many-valued, non-monotonic, supervaluationist, dynamic and inquisitive logics, using both model-theoretic and proof-theoretic approaches) and other formal tools (causal inference, game theory, computer simulations and other computational tools), and combine these tools with philosophical reflection and linguistic analysis. [Go to overview of people affiliated to this Unit]

Natural Language Processing and Digital Humanities (NLP&DH)

Research in the Natural Language Processing and Digital Humanities unit focuses on automated analysis, interpretation and generation of human language and their extension towards language technology. Our work encompasses a range of topics within natural language processing (NLP), such as syntactic parsing, computational semantics and pragmatics, discourse processing, dialogue modelling, machine translation and multilingual NLP.

Our interdisciplinary focus, incorporating insights from linguistics, cognitive science, psychology and machine learning, gives our group’s research a unique profile, having led to numerous distinctive contributions over four decades. Whilst well-known for its influential research in the areas of statistical parsing, syntax based machine translation and semantic role labeling, recently the group has pioneered methods for interpretability of neural models, graph neural networks for NLP and few-shot learning applied to NLP tasks.

Another prominent research direction focuses on the development of societally-oriented and responsible NLP technology, as well as applications in digital humanities, media studies and computational social science. To this end, the group has explored how statistical and neural models can retrieve information from text to help answer questions in the humanities, ranging from history to philosophy, and aid large-scale data-driven analysis of cultural artifacts. [Go to overview of people affiliated to this Unit]

Epistemology and Philosophy of Science (EPS)

Researchers in this unit focus on the use of computational models and analytic methods coming from logic, probability theory and game theory to address a number of topics in formal epistemology and in the methodology and philosophy of science broadly conceived.

Within epistemology, our team plays a leading role in the design and use of epistemic and doxastic logics, with highlights on dynamic interactive belief revision and applications of logic to opinion diffusion in social networks. The team’s study of rational agency draws connections to work on multi-agent systems in AI, as well as to investigations on the theory of mind in the cognitive sciences.

Within the methodology and philosophy of science, the team focuses on scientific explanation and methods applied to areas such as AI, Mathematics, Quantum Physics, Cognitive Science, Life Science and the Engineering Sciences. Core topics range from function modelling in the engineering sciences to models of responsible agency in philosophy of AI as well as a logic-based analysis of quantum information.

The unit is a key player in the newly developed area of computational philosophy, conceived in two manners: the application of data-driven, computational methods from AI in the investigation of the development of scientific ideas (concept drift), in particular ideas from logic and methodology, and methodological reflections on computational linguistics and natural language processing seeing as a new research domain in the philosophy of science. [Go to overview of people affiliated to this Unit]

Language and Music Cognition (LMC)

The Language and Music Cognition unit uses computational models and artificial intelligence to study questions of semantics and meaning, both linguistic and musical, and tests the behavioural implications of these models for speakers, signers, musicians, readers, and listeners.

One important line of research focusses on our capacity for music (i.e., musicality), defined as a natural, spontaneously developing set of traits that are based on and constrained by our cognitive abilities, and its underlying biology. The group also explores the learnability and evolution of language, in particular how the uniquely human propensity to use complex expressions to convey complex meanings came about. Complexity itself is a priority for the unit as a means of understanding core cognitive abilities such as language learning, comprehension, or reasoning. Other work explores the cognitive boundaries between language and music, for example, delineating the conditions under which the speech-to-song illusion can occur.

Machine learning and representations are key to several unit member’s methodologies, for example, measuring the musical characteristics of ‘catchy’ music, modelling visually grounded language use, or explaining linguistic universals. The group works with diverse and multimodal data, both symbolic and subsymbolic, correlational and experimental, audio/video and text. [Go to overview of people affiliated to this Unit]

Theoretical Computer Science (TCS)

In theoretical computer science, our research is characterised by a focus on fundamental questions regarding the design and analysis of algorithms. We investigate problems motivated by applications in physics, economics, and AI.

Specifically, at the interface with physics, we conduct research in quantum computing and quantum information. At the interface with economics, we are active in the fields of algorithmic game theory and computational social choice. Finally, at the interface with AI, we work on topics in knowledge representation and multiagent systems.

Transcending this diversity of research directions is a shared reliance on formal tools, including techniques originating in computational logic, complexity theory, information theory, linear algebra, combinatorics, and discrete mathematics more generally. [Go to overview of people affiliated to this Unit]