Abstract
In this paper we will show that certain networks called inhibition nets may be regarded as cognitive agents drawing nonmonotonic inferences. It will be proven that the system CL of nonmonotonic logic is both sound and complete with respect to the inferences drawn by finite hierarchical inhibition nets. The latter class of inhibition nets is shown to correspond to the class of finite, normal, hierarchical logic programs concerning dynamics, and also to the class of binary, layered, input-driven artificial neural networks.
Item Type: | Journal article |
---|---|
Keywords: | Nonmonotonic reasoning; Networks; Inhibition; Cognitive agents; Cumulativity; Logic programs; Artificial neural networks |
Faculties: | Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) Philosophy, Philosophy of Science and Religious Science > Munich Center for Mathematical Philosophy (MCMP) > Logic |
Subjects: | 100 Philosophy and Psychology > 160 Logic |
ISSN: | 1872-7921 |
Language: | English |
Item ID: | 49643 |
Date Deposited: | 28. May 2018, 12:42 |
Last Modified: | 04. Nov 2020, 13:27 |