24 research outputs found
Scheduling Games with Machine-Dependent Priority Lists
We consider a scheduling game in which jobs try to minimize their completion
time by choosing a machine to be processed on. Each machine uses an individual
priority list to decide on the order according to which the jobs on the machine
are processed. We characterize four classes of instances in which a pure Nash
equilibrium (NE) is guaranteed to exist, and show, by means of an example, that
none of these characterizations can be relaxed. We then bound the performance
of Nash equilibria for each of these classes with respect to the makespan of
the schedule and the sum of completion times. We also analyze the computational
complexity of several problems arising in this model. For instance, we prove
that it is NP-hard to decide whether a NE exists, and that even for instances
with identical machines, for which a NE is guaranteed to exist, it is NP-hard
to approximate the best NE within a factor of for all
. In addition, we study a generalized model in which players'
strategies are subsets of resources, each having its own priority list over the
players. We show that in this general model, even unweighted symmetric games
may not have a pure NE, and we bound the price of anarchy with respect to the
total players' costs.Comment: 19 pages, 2 figure
LP-based covering games with low price of anarchy
We design a new class of vertex and set cover games, where the price of anarchy bounds match the best known constant factor approximation guarantees for the centralized optimization problems for linear and also for submodular costs. This is in contrast to all previously studied covering games, where the price of anarchy grows linearly with the size of the game. Both the game design and the price of anarchy results are based on structural properties of the linear programming relaxations. For linear costs we also exhibit simple best response dynamics that converge to Nash equilibria in linear time