Tomorrow’s seminar is again about parameter tuning. This time, we’ll discuss the paper «From Adaptive to More Dynamic Control in Evolutionary Algorithms», by Di Tollo et al., presented last week at the Evo* congress, in Torino. Here’s the abstract:
Adaptive evolutionary algorithms have been widely developed to improve the management of the balance between intensification and diversification during the search. Nevertheless, this balance may need to be dynamically adjusted over time. Based on previous works on adaptive operator selection, we investigate in this paper how an adaptive controller can be used to achieve more dynamic search scenarios and what is the real impact of possible combinations of control components. This study may be helpful for the development of more autonomous and efficient evolutionary algorithms.
GeNeura Team 