We propose a simple approach to visualising the time behaviour of Random Boolean Networks (RBNs), and demonstrate the approach by examining the effect of canalising functions for ...
Abstract. We propose the use of Deterministic Generalized Asynchronous Random Boolean Networks [1] as models of contextual deterministic discrete dynamical systems. We show that ch...
A number of representation schemes have been presented for use within Learning Classifier Systems, ranging from binary encodings to neural networks. This paper presents results fr...
Boolean satisfiability (SAT) is the canonical NP-complete problem that plays an important role in AI and has many practical applications in Computer Science in general. Boolean n...
Randomly connecting networks have proven to be universal computing machines. By interconnecting a set of nodes in a random way one can model very complicated non-linear dynamic sy...