An algorithm independent metric is introduced that measures the dispersion of a uniform random sample drawn from the top ranked percentiles of the search space. A low dispersion f...
Bayesian forecasting models provide distributional estimates for random parameters, and relative to classical schemes, have the advantage that they can rapidly capture changes in ...
We investigated how indexed FOR-loops, such as the ones found in procedural programming languages, can be implemented in genetic programming. We use them to train programs that le...
Our previous work has introduced a hyperheuristic (HH) approach based on Genetic Programming (GP). There, GP employs usergiven languages where domain-specific local heuristics ar...
Abstract We describe a method to approximate a segment of the intersection curve of two implicitly defined surfaces by a rational parametric curve. Starting from an initial soluti...