— If a population of programs evolved not for a few hundred generations but for a few hundred thousand or more, could it generate more interesting behaviours and tackle more comp...
Learning Classifier Systems use evolutionary algorithms to facilitate rule- discovery, where rule fitness is traditionally payoff based and assigned under a sharing scheme. Most c...
To complement standard fitness functions, we propose "Fitness Importance" (FI) as a novel meta-heuristic for online learning systems. We define FI and show how it can be...
We consider multitask learning of visual concepts within genetic programming (GP) framework. The proposed method evolves a population of GP individuals, with each of them composed...
Wojciech Jaskowski, Krzysztof Krawiec, Bartosz Wie...
Genetic programming has been considered a promising approach for function approximation since it is possible to optimize both the functional form and the coefficients. However, it...