Details of Grant 

EPSRC Reference:	GR/S26569/01
Title:	Computational modelling of quantifiers; The relative influence of scalar and contextual factors.
Principal Investigator:	Coventry, Professor K
Other Investigators:	Cangelosi, Professor A Newstead, Professor S
Researcher Co-Investigators:
Project Partners:
Department:	Sch of Psychology
Organisation:	University of Plymouth
Scheme:	Standard Research (Pre-FEC)
Starts:	19 November 2003	Ends:	18 November 2005	Value (£):	141,752
EPSRC Research Topic Classifications:	Cognitive Science Appl. in ICT Human Communication in ICT
EPSRC Industrial Sector Classifications:	Creative Industries
Related Grants:
Panel History:
Summary on Grant Application Form
The idea that quantifers like 'few', 'some', 'many, and 'most somehow refer to a number of objects which is easily quantifiable has been challenged by a battery of empirical findings which show that the number referred to varies as a function of a range of contextual factors (e.g., expected frequency, relative size, set size and functionality). However, to date, despite the range of applications that require the instantiation of quantifiers, computational models dealing with quantifiers have in the main failed to consider the experimental evidence, and rarely do they mention psychological plausibility. The main purpose of the present programme of research is to develop a psychologically plausible computational model for vague quantifiers which maps onto real psychological data. Therefore the present proposal aims to collect experimental data in order to establish the relative influence of a range of scalar and contextual varialbles on the comprehension of quantifiers, and to test a connectionist model against these data. The model, which takes visual scenes as input, will build on routines we have developed on GR/N38145, with the addition of a range of new routines to calculate a range of contextual variables. The end result of this short programme of work will be a working computational model for vague quantifiers and a battery of experimental results regarding the relative importance of contextual variables. The model will also make predictions which will themselves be tested empirically.
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Organisation Website:	http://www.plym.ac.uk