Abstract. With the huge increase in the volume of information available in digital form and the increasing diversity of Web applications, the need for efficient, reliable, informat...
Cooperative coevolution has proven to be a promising technique for solving complex combinatorial optimization problems. In this paper, we present four different strategies which i...
Leonardo Vanneschi, Giancarlo Mauri, Andrea Valsec...
Sampling functions in Gaussian process (GP) models is challenging because of the highly correlated posterior distribution. We describe an efficient Markov chain Monte Carlo algori...
Michalis Titsias, Neil D. Lawrence, Magnus Rattray
The main purpose of this paper is to propose an incorporating a grammatical evolution (GE) into the genetic algorithm (GA), called GEGA, and apply it to estimate the compressive s...
Hsun-Hsin Hsu, Li Chen, Chang-Huan Kou, Tai-Sheng ...
RRL is a relational reinforcement learning system based on Q-learning in relational state-action spaces. It aims to enable agents to learn how to act in an environment that has no ...