This paper deals with the problem of comparing and testing evolutionary algorithms, that is, the benchmarking problem, from an analysis point of view. A practical study of the app...
We present quantitative models for the selection pressure on cellular evolutionary algorithms structured as a ring of cells. We obtain results for synchronous and asynchronous cell...
Mario Giacobini, Marco Tomassini, Andrea Tettamanz...
We introduce a clustering-based method of subpopulation management in genetic programming (GP) called Evolutionary Tree Genetic Programming (ETGP). The biological motivation behin...
In this paper, we present an empirical comparison of the effects of category skew on six feature selection methods. The methods were evaluated on 36 datasets generated from the 20...
In reinforcement learning, an agent interacting with its environment strives to learn a policy that specifies, for each state it may encounter, what action to take. Evolutionary c...