The notion of optimality naturally arises in many areas of applied mathematics and computer science concerned with decision making. Here we consider this notion in the context of two formalisms used for different purposes and in different research areas: graphical games and soft constraints. We relate the notion of optimality used in the area of soft constraint satisfaction problems (SCSPs) to that used in graphical games, showing that for a large class of SCSPs that includes weighted constraints every optimal solution corresponds to a Nash equilibrium that is also a Pareto efficient joint strategy. We also study alternative mappings including one that maps graphical games to SCSPs, for which Pareto efficient joint strategies and optimal solutions coincide. © 2008 Springer Berlin Heidelberg.
CITATION STYLE
Apt, K. R., Rossi, F., & Venable, K. B. (2008). A comparison of the notions of optimality in soft constraints and graphical games. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5129 LNAI, pp. 1–16). Springer Verlag. https://doi.org/10.1007/978-3-540-89812-2_1
Mendeley helps you to discover research relevant for your work.