Talks and Poster Presentations (with Proceedings-Entry):
M. Kronegger, M. Lackner, A. Pfandler, R. Pichler:
"A Parameterized Complexity Analysis of Generalized CP-Nets";
Talk: Twenty-Eighth AAAI Conference on Aritifical Intelligence (AAAI 2014),
Québec City, Québec, Canada;
- 07-31-2014; in: "Proceedings of the Twenty-Eighth AAAI Conference on Aritifical Intelligence",
C. Brodley, P. Stone (ed.);
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.
Project Head Reinhard Pichler:
Effiziente, parametrisierte Algorithmen in Künstlicher Intelligenz und logischem Schließen
Created from the Publication Database of the Vienna University of Technology.