@inproceedings{KroneggerLPP14-pc,
  author    = {Martin Kronegger and Martin Lackner and Andreas Pfandler and Reinhard Pichler},
  title     = {A Parameterized Complexity Analysis of Generalized {CP}-Nets},
  booktitle = {Proc. of the 28th AAAI Conference on Artificial Intelligence (AAAI-14)},
  year      = {2014},
  pages     = {1091-1097},
  publisher = {AAAI Press},
  abstract  = {Generalized CP-nets (GCP-nets) allow a succinct representation of preferences over multi-attribute domains. As a consequence of their succinct representation, many GCP-net related tasks are computationally hard. Even finding the more preferable of two outcomes is PSPACE-complete. In this work, we employ the framework of parameterized complexity to achieve two goals: First, we want to gain a deeper understanding of the complexity of GCP-nets. Second, we search for efficient fixed-parameter tractable algorithms.}
}