This type of model does not ascribe probabilistic knowledge to speakers.
At this point we may usefully distinguish between deterministic grammar and probabilistic grammar.
A probabilistic analysis can ascertain how common inconsistency is for different aggregation and decision rules.
For the probabilistic approach, we rely on a training corpus of example sentences with their main topics manually assigned to them.
The application interesting us here is the possibility of establishing an extension to probabilistic relations.
We choose to deal with the more general notion of a real cone because its equational theory is nicer than the theory of probabilistic choice.
We are going to study a more general equational theory, which subsumes the theory of probabilistic choice.
We only treat the case of generative probabilistic automata here, although most results should be adaptable to other settings.
