The current work addresses the development of cognitive abilities in artificial organisms. In the proposed approach, neural network-based agent structures are employed to represen...
Abstract- Finding Golomb rulers is an extremely challenging optimization problem (with many practical applications) that has been approached by a variety of search methods in recen...
Information distance is used to measure how similar sensorimotor experience is to past experience within a certain temporal horizon. Applied to groups of sensors this gives a mathe...
Naeem Assif Mirza, Chrystopher L. Nehaniv, Kerstin...
This paper presents a practical methodology of improving the efficiency of Genetic Algorithms through tuning the factors significantly affecting GA performance. This methodology is...
Andrei Petrovski, Alexander E. I. Brownlee, John A...
Co-evolutionary algorithms (CEAs) have been applied to optimization and machine learning problems with often mediocre results. One of the causes for the unfulfilled expectations i...
Abstract- Evolutionary Algorithms (EAs) have the tendency to converge quickly into a single solution in the search space. However, many complex search problems require the identi...
Abstract- We introduce metrics on sensorimotor experience at various temporal scales based on informationtheory. Sensorimotor variables through which the experience of an agent fl...
Abstract- Choosing the best parameter setting is a wellknown important and challenging task in Evolutionary Algorithms (EAs). As one of the earliest parameter tuning techniques, th...
Genetic algorithms (GAs) and evolution strategies (ESs) are two widely used evolutionary algorithms. The main differences between GAs and ESs lie in their representations and varia...