Using learning classifier systems to design selective hyper-heuristics for constraint satisfaction problems

Constraint satisfaction problems (CSP) are defined by a set of variables, where each variable contains a series of values it can be instantiated with. There is a set of constraints among the variables that restrict the different values they can take simultaneously. The task is to find one assignment to all the variables without breaking any constraint. To… (More)