Abstract. Theoretical models of Turing complete linear genetic programming (GP) programs suggest the fraction of halting programs is vanishingly small. Convergence results proved f...
In this paper we demonstrate that pressure for robustness combined with function sets containing redundant genes can cause an evolutionary system to avoid a more fit solution in f...
—A Bayesian-based methodology is presented which automatically penalizes overcomplex models being fitted to unknown data. We show that, with a Gaussian mixture model, the approac...
Stephen J. Roberts, Dirk Husmeier, Iead Rezek, Wil...
We present a combinatorial framework for the study of a natural class of distributed optimization problems that involve decisionmaking by a collection of n distributed agents in th...
This paper presents a novel technique to perform global optimization of communication and preprocessing calls in the presence of array accesses with arbitrary subscripts. Our sche...