In this research work a large set of the classical numerical functions were taken into account in order to understand both the search capability and the ability to escape from a lo...
Vincenzo Cutello, Giuseppe Nicosia, Mario Pavone, ...
This paper introduces a novel study on the sense of valency as a vital process for achieving adaptation in agents through evolution and developmental learning. Unlike previous stud...
— This paper discusses utilizing genetic algorithms to automatically design a suitable sensor morphology and controller for a given task in categories of environments. The type o...
This research addresses the formation of new concepts and their corresponding ontology in a multiagent system where individual autonomous agents try to learn new concepts by consu...
We show how the understandability and speed of genetic programming classification algorithms can be improved, without affecting the classification accuracy. By analyzing the dec...