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...
We present a novel linear clustering framework (DIFFRAC) which relies on a linear discriminative cost function and a convex relaxation of a combinatorial optimization problem. The...
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...
This paper describes a speciation method that allows an evolutionary process to learn several robot behaviors using a single execution. Species are created in behavioral space in ...
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...