The inherent and increasing complexity, heterogeneity and unpredictability of computer networks make the task of managing these systems highly complex. The autonomic computing paradigm brings innovative solutions to the network management area with new adaptable and "clever" solutions which should consider a heterogeneous functionality in a wide variety of fields. One of the challenges involved in proposing autonomic solutions for quality of service management consists of dealing with the inherent complexity and proposing solutions with feasible execution time. In brief, the autonomic solution effective response time should be fast enough so that it could be applied before any new important network state change. In this paper, a framework that uses artificial intelligence techniques and self-partitioning methods is considered as the basis for evaluating a solution to the problem of dynamic LSPs setup allocation in a general MPLS network topology focusing on keeping a low comp...