Compositional Approaches for Physics, NLP, and Social Sciences
Compositional Approaches for Physics, NLP, and Social Sciences (CAPNS 2018) will be colocated with QI 2018. The workshop is a continuation and extension of the Workshop on Semantic Spaces at the Intersection of NLP, Physics and Cognitive Science held in June 2016.
Aims and Scope
The ability to compose parts to form a more complex whole, and to analyze a whole as a combination of elements, is desirable across disciplines. In this workshop we bring together researchers applying compositional approaches to physics, NLP, cognitive science, and game theory.
Within NLP, a long-standing aim is to represent how words can combine to form phrases and sentences. Within the framework of distributional semantics, words are represented as vectors in vector spaces. The categorical model of Coecke et al. , inspired by quantum protocols, has provided a convincing account of compositionality in vector space models of NLP. There is furthermore a history of vector space models in cognitive science. Theories of categorization such as those developed by Nosofsky  and Smith et al.  utilise notions of distance between feature vectors. More recently Gärdenfors [2004, 2014] has developed a model of concepts in which conceptual spaces provide geometric structures, and information is represented by points, vectors and regions in vector spaces. The same compositional approach has been applied to this formalism, giving conceptual spaces theory a richer model of compositionality than previously [Bolt et al., 2018].
Compositional approaches have also been applied in the study of strategic games and Nash equilibria. In contrast to classical game theory, where games are studied monolithically as one global object, compositional game theory works bottom-up by building large and complex games from smaller components. Such an approach is inherently difficult since the interaction between games has to be considered. Research into categorical compositional methods for this field have recently begun [Ghani et al., 2018].
Moreover, the interaction between the three disciplines of cognitive science, linguistics and game theory is a fertile ground for research. Game theory in cognitive science is a well-established area [Camerer, 2011]. Similarly game theoretic approaches have been applied in linguistics [Jäger, 2008]. Lastly, the study of linguistics and cognitive science is intimately intertwined [Smolensky and Legendre, 2006, Jackendoff, 2007]. Physics supplies compositional approaches via vector spaces and categorical quantum theory, allowing the interplay between the three disciplines to be examined. Commonalities between the compositional mechanisms employed will be extracted, and applications and phenomena traditionally thought of as ‘non-compositional’ will be examined.
Topics of interests include (but are not restricted to):
- Applications of quantum logic in natural language processing and cognitive science
- Compositionality in vector space models of meaning
- Compositionality in conceptual spaces
- Compositional approaches to game theory and social sciences
- Reasoning in vector spaces and conceptual spaces
- Conceptual spaces in linguistics
- Game-theoretic models of language and conceptual change
- Logics for social behaviour
- Diagrammatic reasoning for natural language processing, cognitive science, and game theory
- Compositional explanations of so-called 'non-compositional' phenomena such as metaphor
Paul Smolensky, Principal Researcher, Microsoft Research, and Krieger-Eisenhower Professor of Cognitive Science, Johns Hopkins University