Name
Abstract | ||
|---|---|---|
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. |
Year | Venue | Field |
|---|---|---|
2016 | CoRR | Convergence (routing),Categorical variable,Computer science,Artificial intelligence,Natural language processing,Hedge (finance),Machine learning |
DocType | Volume | Citations |
Journal | abs/1601.06755 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Martha Lewis | 1 | 27 | 4.06 |
| Jonathan Lawry | 2 | 172 | 19.06 |