Space of Reasons and Mathematical Model
  Inferential relations govern our concept use. In order to understand a
concept it has to be located in a space of implications. There are different
kinds of conditions for statements, i.e. that the conditions represent
different kinds of explanations, e.g. causal or conceptual explanations. The
crucial questions is: How can the conditionality of language use be
represented. The conceptual background of representation in models is discussed
and in the end I propose how implications of propositional logic and conceptual
determinations can be represented in a model of a neural network.
