ILLC

Institute for Logic, Language and Computation

The Institute for Logic, Language and Computation (ILLC) is a research institute of the University of Amsterdam in which researchers from the Faculty of Science (FNWI) and the Faculty of Humanities (FGW) collaborate. Research within the ILLC is focused on the fundamental principles of encoding, transmission, and comprehension of information. Emphasis is on natural and formal languages, but other information carriers, such as images and music, are studied as well. Research at ILLC is interdisciplinary, and aims to bring together insights from various disciplines concerned with information and information processing, such as logic, mathematics, computer science, linguistics, cognitive science, artificial intelligence, and philosophy.

Read more about ILLC and ILLC research on their website

ILLC research lines within the CSCA

Logic, psychology of reasoning, and the brain
Semantics in cognitive perspective
Interaction and cognition
Modelling learning
Music cognition
Cognitive models of language, music and vision
The unsupervised mind

Logic, psychology of reasoning, and the brain

Programme coordinator: Prof. dr. Michiel van Lambalgen
Contact: M.vanLambalgen (at) uva.nl

Subject: The main aim of ILLC's investigations on reasoning is to show that logical languages can be fruitfully used as high-level specifications of cognitive functions, and mathematical logic can be used in explaining human reasoning behaviour. To achieve these goals, logical and computational models are paired with methods from empirical psychology and neuroscience in an innovative way. The empirical investigations concern both healthy and cognitively impaired subjects.

Key publications:

Blutner, K.R. (2004). Nonmonotonic inferences and neural networks. Synthese 141, 143-174.
Klaassen, P., E. Rietveld, J. Topal, (2006). Gesitueerde normativiteit: van Wittgenstein naar neurofenomenologie. Algemeen Nederlands Tijdschrift voor Wijsbegeerte 98, 1-17.
Stenning, K. and M. van Lambalgen, (2005). Semantic interpretation as computation in nonmonotonic logic: the real meaning of the suppression task. Cognitive Science 29, 919 -960.

Semantics in cognitive perspective

Programme coordinator: Prof. dr. Jeroen Groenendijk
Contact: J.A.G.Groenendijk (at) uva.nl

Subject: Starting point of this programme is the conviction that semantic explanations must be informed by cognitive considerations. In particular, the semantics of tense and aspect is studied from the point of view of human event-coding and time-perception. Another question of interest here is how different moods (declarative imperative, interrogative) can be distinguished in an overall dynamic framework in which meaning of an utterance is equated with the change it brings about in the hearer's cognitive state.

Key publications:

Groenendijk, J.A.G., & Stokhof, M.J.B. (2000). Meaning in motion. In K. von Heusinger and U. Egli, eds., Reference and Anaphorical Relations, 47-76. Dordrecht: Kluwer.
Lambalgen, M. van, and F. Hamm (2004). The Proper Treatment of Events. Blackwell, Oxford.
Veltman, F.J.M.M. (2005). Making counterfactual assumptions. Journal of Semantics, 22, 159-180.

Interaction and cognition

Programme coordinator: Prof. dr. Johan van Benthem
Contact: J.vanBenthem (at) uva.nl

Subject: In the past decade it has become increasingly clear that studying information first and foremost means studying information exchange. More generally, information exchange is a form of interaction where agents act together in strategic ways. In particular, interaction is crucial to intelligent behaviour in the field of natural language. Notions from game theory, in particular evolutionary games, are being used today to answer all kinds of questions with cognitive relevance, such as the question how linguistic conventions can arise.

Key publications:

van Rooij, R.A.M. (2004). Evolution of conventional meaning and conversational principles. Synthese, 139, 331-366.
Blutner, K.R., H. de Hoop, H., and P.C.J. Hendriks (2005). Optimal Communication. CSLI, Stanford.
van Benthem, J.F.A.K. (to appear). Cognition as Interaction, G. Bouma and I. Krämer, eds., Cognitive Foundations of Interpretation. KNAW, Amsterdam.

Modelling learning

Programme coordinator: Prof. dr. Remko Scha
Contact: Scha (at) uva.nl

Subject: Within ILLC particular attention is paid to the modelling of the learning process. Several techniques are studied. For language learning the focus is on the 'Data-Oriented Parsing' model, which we developed over the last fifteen years. Current research involves improving the probability estimations of the model, enriching its linguistic coverage, and putting semantic representations into the picture. This enables us to move toward models of first language acquisition.

Key publications:

Bod, R., R. Scha, and K. Sima'an (2003). Data-Oriented Parsing. CSLI Publications, Stanford.
Leskes, B. and L. Torenvliet (to appear). The value of agreement: a new boosting algorithm. Journal of Computer and System Sciences.

Music cognition

Programme coordinator: Dr. Henkjan Honing
Contact: H.J.Honing (at) uva.nl

Subject: ILLC's research is concerned with the computational modeling of music perception and production with a special focus on the temporal aspects of music such as rhythm, timing, and tempo. Recent topics are concerned with the role of perception, attention, and memory in music listening, as well as the role of these cognitive mechanisms in the origins of music.

Key publications:

Honing, H. & Ladinig, O. (2009). Exposure influences expressive timing judgments in music. Journal of Experimental Psychology: Human Perception and Performance, 35(1) 281-288.
Winkler, I., Haden, G., Ladinig, O., Sziller, I., Honing, H. (2009). Newborn infants detect the beat in music. Proceedings of the National Academy of Sciences, 106, 2468-2471.
Honing, H. (2006). Computational modeling of music cognition: a case study on model selection. Music Perception 23, 365-376

Cognitive Models of Language, Music and Vision

Programme coordinator: Prof. dr. Rens Bod
Contact: rens (at) science.uva.nl

Subject: The human cognitive system organizes perceptual information into hierarchical descriptions that can be represented by tree structures. Tree structures have been used to describe linguistic, musical and visual perception. This research line investigates the commonalities between the different forms of perception and aims at developing a general underlying mechanism that governs all perceptual organization. Such a unified mechanism may solve a small part of Alan Newell's famous challenge to create a single model for all cognitive behavior.

Key publications:

Bod, R. (2002). A Unified Model of Structural Organization in Language and Music. Journal of Artificial Intelligence Research, 17(2002): 289-308.
Honingh, A. and R. Bod (2005). Convexity and the Well-formedness of Musical Objects. Journal of New Music Research, 34(3), 293-303.
Borensztajn, G., J. Zuidema and R. Bod (2008). Children's grammars grow more abstract with age - Evidence from an automatic procedure for identifying the productive units of language. Proceedings CogSci 2008. Washington D.C.

The Unsupervised Mind

Programme coordinator: Prof. dr. Rens Bod
Contact: rens (at) science.uva.nl

Subject: Unsupervised learning has become one of the major research areas in computational cognition. This project develops unsupervised models of cognitive tasks such as language learning and problem-solving. We employ a probabilistic, exemplar-based view on cognition which induces statistical generalizations from raw, unannotated data. Unsupervised learning models nowadays compete with supervised learning, contributing to the nativism-empiricism debate in cognitive science.

Key publications:

R. Bod (2008). The Data-Oriented Parsing Approach: Theory and Application. In J. Fulcher and L. Jain (eds.), Handbook of Computational Intelligence, Springer, 34-78.
R. Bod, H. Fitz and W. Zuidema (2006). On the Structural Ambiguity in Natural Language that the Neural Architecture Cannot Deal With. Behavioral and Brain Sciences, 29(1).
Yoav Seginer (2007), Fast Unsupervised Incremental Parsing. In Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics. 384-391.