In this paper we present the Dinosaur Hypothesis, which states that the behaviour of a market never settles down and that the population of predictors continually co-evolves with t...
Michael Kampouridis, Shu-Heng Chen, Edward P. K. T...
Abstract. While traditional approaches to machine learning are sensitive to highdimensional state and action spaces, this paper demonstrates how an indirectly encoded neurocontroll...
Using unconstrained binary quadratic programming problem as a case study, we investigate the role of multi-parent crossover operators within the memetic algorithm framework. We eva...
The hypervolume indicator is widely used to guide the search and to evaluate the performance of evolutionary multi-objective optimization algorithms. It measures the volume of the ...
Abstract. In recent years, there has been a growing interest in addressing dynamic optimization problems (DOPs) using evolutionary algorithms (EAs). Several approaches have been de...