Abstract. This paper is concerned with a dynamic vehicle routing problem. The problem is dynamic in the sense that the time it will take to traverse each edge is uncertain. The pro...
Abstract. A scheduling algorithm for satellites imaging tasks in a dynamic and uncertain environment. The environment is dynamic in the sense that imaging tasks will be added or re...
This paper introduces subchromosome representations to the linkage learning genetic algorithm (LLGA). The subchromosome representation is utilized for effectively lowering the num...
Abstract. A model of coevolutioinary genetic algorithms (COGA) consisting of two populations coevolving on two-bit landscapes is investigated in terms of the effects of random par...
Ming Chang, Kazuhiro Ohkura, Kanji Ueda, Masaharu ...
Abstract. The performance of classification algorithms in machine learning is affected by the features used to describe the labeled examples presented to the inducers. Therefore,...
Abstract. The usual approach to deal with noise present in many realworld optimization problems is to take an arbitrary number of samples of the objective function and use the samp...
A model of the dynamics of solving the counting-ones (OneMax) problem using a simple genetic algorithm (GA) is developed. It uses statistics of the early generations of GA runs to ...
Nowadays, large distributed databases are commonplace. Client applications increasingly rely on accessing objects from multiple remote hosts. The Internet itself is a huge network ...
This paper introduces a gradient-based reward prediction update mechanism to the XCS classifier system as applied in neuralnetwork type learning and function approximation mechani...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi
It has been shown empirically that the XCS classifier system solves typical classification problems in a machine learning competitive way. However, until now, no learning time es...
Martin V. Butz, David E. Goldberg, Pier Luca Lanzi