… The machine learning systems discussed in this paper are called classifier systems. It is …
point of view of classifier systems: At the lowest level is the performance system. This is the …

… Another area that has drawn attention is the development of what we will call “multilearning
classifier systems” (M-LCSs) (ie, multiagent LCSs, ensemble LCSs, and distributed LCSs), …

… and, t)articularly, classifier systems, the learning problem faced by … , classifier systems
satisfy the constraints, but tests have been limited. We show how the standard classifier system …

… Learning classifier systems (LCSs) are rulebased systems … sequential decision problem-solving
systems endowed with a … be seen as learning systems building a compact representation …

… This paper provides a review of the field of MultiClassifier Systems and presents simple
details and instructions for the construction of a MCS. There is currently a lot of literature on MCS …

… based on the combination of outputs of a set of different classifiers have been proposed as
… classification systems. In this paper, the problem of design of multiple classifier system is …

… A multiple classifier system is justified only if the combined decisions are better than those
of any single classifier in the system. The comparison of performance can be based on two …

… classifier systems such as: data mining, medical data analysis, economic trading agents,
aircraft maneuvering, and autonomous robotics. A classifier systems … learning classifier systems …

… approaches based on single classifiers. This paper presents an up-to-date survey on
multiple classifier system (MCS) from the point of view of Hybrid Intelligent Systems. The article …

… Being the eighth in a well-established series of meetings providing an international forum
for the discussion of issues in multiple classifier system design, the workshop achieved its …