Computer programming of complex systems is a time consuming effort. Results are often brittle and inflexible. Evolving, self-learning flexible multi-agent systems remain a distant ...
An adaptive boosting ensemble algorithm for classifying homogeneous distributed data streams is presented. The method builds an ensemble of classifiers by using Genetic Programmi...
Gianluigi Folino, Clara Pizzuti, Giandomenico Spez...
Model- and simulation-designers are often interested not in the optimum output of their system, but in understanding how the output is sensitive to different parameters. This can...
Sean Luke, Deepankar Sharma, Gabriel Catalin Balan
The problem of production and delivery lot-sizing and scheduling of set of items in a two-echelon supply chain over a finite planning horizon is addressed in this paper. A single ...
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...