In this monograph the authors introduce a novel fuzzy rule-base referred to as the Fuzzy
All-permutations Rule-Base (FARB). They show that inferring the FARB using standard tools from
fuzzy logic theory yields an input-output map that is mathematically equivalent to that of an
artificial neural network. Conversely every standard artificial neural network has an
equivalent FARB. The FARB-ANN equivalence integrates the merits of symbolic fuzzy rule-bases
and sub-symbolic artificial neural networks and yields a new approach for knowledge-based
neurocomputing in artificial neural networks.
