A non-dominated sorting genetic algorithm is used to evolve models of learning from different theories for multiple tasks. Correlation analysis is performed to identify parameters...
Abstract. While traditional approaches to machine learning are sensitive to highdimensional state and action spaces, this paper demonstrates how an indirectly encoded neurocontroll...
— The paper proposes a hypernetwork-based method for stock market prediction through a binary time series problem. Hypernetworks are a random hypergraph structure of higher-order...
Elena Bautu, Sun Kim, Andrei Bautu, Henri Luchian,...
Humans tend to group together related properties in order to understand complex phenomena. When modeling large problems with limited representational resources, it is important to...
We simulate the evolution of a domain vocabulary in small communities. Empirical data show that human communicators can evolve graphical languages quickly in a constrained task (P...