We present the first comparison between properties of clusters galaxies detected by eROSITA Final Equatorial-Depth Survey (eFEDS) and XMM Cluster (XCS). have compared, in an ensemble fashion, from eFEDS X-ray cluster catalogue with those Ultimate eXtragaLactic (XXL) survey project (XXL-100-GC). find distributions redshift temperature ($T_{\rm X}$) to be broadly similar two surveys, a larger pro...

XCS [1][2] represents a new form of Learning Classifier System [3] that uses accuracy as a means of guiding fitness for selection within a Genetic Algorithm. The combination of accuracy-based selection and a dynamic niche-based deletion mechanism achieve a long sought-after goal – the reliable production, maintenance, and proliferation of the sub-population of optimally general accurate classif...

Learning classifier systems represent a technique by which various characteristics of a given problem space may be deduced and presented to the user in a readable format. In this paper we present results from the use of XCS on simple tasks with the general multi-variable features typically found in problems addressed by an Interactive Evolutionary Design process. That is, we examine the behavio...

In investigating the Consecutive State Problem within XCS (Barry, 1999) it was suggested that a possible solution lay in allowing the XCS to persist with a single action over the aliased states. It was shown that this technique was sufficient to overcome the Consecutive State Problem as long as mechanisms were also provided which prevented the persistent application of 'Null Actions'. An altern...

The classiier system XCS was investigated for data mining applications where the dataset discrimination surface (DS) is generally oblique to the attribute axes. Despite the classiiers' hyper-rectangular predicates, XCS reached 100% performance on synthetic problems with diagonal DS's and, in a train/test experiment, competitive performance on the Wisconsin Breast Cancer dataset. Final classiier...

This paper puts forward a model of Extended Client/Server (XCS) system, which is based on traditional Client/Server Architecture and borrows such merits from Browser/Server system as integrated code maintenance at Server-end and installation-free at Browser-end, etc. In an XCS system, Client is dynamically configured and automatically updated, and Server is able to commit self-health-checks and...

We present an extension of the learning classifier system XCS in which classifier conditions are represented by RPN expressions and stack-based Genetic Programming is used to recombine and mutate classifiers. In contrast with other extensions of XCS involving tree-based Genetic Programming, the representation we apply here produces conditions that are linear programs, interpreted by a virtual s...

Previous work has studied the use of interval representations in XCS to allow its use in continuous-valued environments. Here we compare the speed of learning of continuous-valued versions of ZCS and XCS with a simple model of an online environment.

Despite two decades of work learning classi er systems researchers have had relatively little to say on the subject of what makes a problem diÆcult for a classi er system. Wilson's accuracy-based XCS, a promising and increasingly popular classi er system, is, we feel, the natural rst choice of classi er system with which to address this issue. To make the task more tractable we limit our consid...