This paper explores the use of a learning classifier system variant, XCS, in learning effective airline decision rules within the context of a multiagent team simulation. From this study a general approach to modeling an airline market has been developed based on a multi-agent, team-based concept. Additionally, several preliminary trials of the simulation have been executed.

This sequel continues the comparison of the twins XCS and SB{XCS. We nd they tend towards di erent representations of the solution and distinguish three types of representations which rule populations can form, namely complete maps, partial maps, and default hierarchies. Following this we evaluate the respective advantages and disadvantages of complete and partial maps at some length. We conclu...

This thesis investigates Learning Classifier System architectures for decision making in continuous-valued domains. The information contained in continuous-valued domains is not always conveniently expressed using the ternary representation typically used by Learning Classifier Systems and an interval-based representation is a natural choice. Two intervalbased representations recently proposed ...

This thesis represents an in depth investigation into the issues raised by the iterative nature of the data-mining process and, in particular, the use of the XCS Learning Classifier System with continuousvalued data-mining problems. The XCS Learning Classifier System has been shown to have the capability for data-mining through rule induction, that is, a technique by which various characteristi...

The XCS Library (XCSLib) is an open source C++ library for genetics-based machine learning and learning classifier systems. It provides (i) several reusable components that can be employed to design new learning paradigms inspired to the learning classifier system principles; and (ii) the implementation of two well-known and widely used models of learning classifier systems.

This paper compares performance of the Pittsburgh-style system GAssist with the Michigan-style system XCS on several datamining problems. Our analysis shows that both systems are suitable for datamining but have different advantages and disadvantages. The study does not only reveal important differences between the two systems but also suggests several structural properties of the underlying da...