  We investigate the emergence of shared concepts in a community of language
users using a multi-agent simulation. We extend results showing that negated
assertions are of use in developing shared categories, to include assertions
modified by linguistic hedges. Results show that using hedged assertions
positively affects the emergence of shared categories in two distinct ways.
Firstly, using contraction hedges like `very' gives better convergence over
time. Secondly, using expansion hedges such as `quite' reduces concept overlap.
However, both these improvements come at a cost of slower speed of development.

Artificial Intelligence;Computation and Language;Multiagent Systems