We analyse the convergence of a GA when the mutation probability is low and the selection pressure is high, for arbitrary crossover types and probabilities. We succeed in mathemat...
We present algorithms for the generation of uniformly distributed Bayesian networks with constraints on induced width. The algorithms use ergodic Markov chains to generate samples....
This paper presents an evolutionary music software system that generates complex rhythmic polyphony in performance. A population of rhythms is derived from analysis of source mater...
act We show how to modelize concurrency between several processors in terms of automata and Markov chains; then, we define a concurrency measure which reflects more faithfully the ...
We describe a simple algorithm based on a Markov chain process to generate simply connected acyclic directed graphs over a fixed set of vertices. This algorithm is an extension of...