Abstract:
We will deal with the representation of conditionals in neural-like networks. One can prove that if the representation of conditionals in networks is "distributed", each of the systems of nonmonotonic logic in Kraus, Lehmann, and Magidor (1990) turns out to be adequate with respect to a corresponding network semantics. We will discuss this result in the context of the debate on symbolic computationalism vs.
connectionism, and we will argue that the best way of interpreting network states that are determined by such conditional representations is in terms of "conditional beliefs" (rather than "beliefs in conditionals").