Nonmonotonic reasoning by inhibition nets

In this paper we will show that certain networks called 'inhibition nors' m ay be regarded as cognitive agents drawing nonmonotonic inferences. It will be proven that the system CL (introduced by KLM in [Artificial Intelligenc e 44 (1990) 186-189]) of nonmonotonic logic is both sound and complete with respect to the inferences drawn by finite hierarchical inhibition nets. Th e latter class of inhibition nets is shown to correspond to the class of fi nite, normal, hierarchical logic programs concerning dynamics, and also to the class of binary, layered, input-driven artificial neural networks. (C) 2001 Elsevier Science B.V. All rights reserved.