Titlebook: Algorithmic Decision Theory; Second International Ronen I. Brafman,Fred S. Roberts,Alexis Tsoukiàs Conference proceedings 2011 Springer-Ver

遍及

chisel

On Minimizing Ordered Weighted Regrets in Multiobjective Markov Decision Processes,ediate reward functions, representing either individual payoffs in a multiagent problem or rewards with respect to different objectives. In this context, we focus on the determination of a policy that fairly shares regrets among agents or objectives, the regret being defined on each dimension as the

noxious

Scaling Invariance and a Characterization of Linear Objective Functions,sign of the selection method. If the representation of valuations of available alternatives is subject to invariance under linear scaling, such as the choice of the unit of measurement, a sensible way to compare choices is to compare weighted sums of individual valuations corresponding to these choi

deceive

Implicit

STRIA

Bribery in Path-Disruption Games,ersaries want to travel from a source vertex to a target vertex. In order to prevent them from doing so, the agents can form coalitions, and a coalition wins if it succeeds in blocking all paths for the adversaries. In this paper, we introduce the notion of bribery for path-disruption games. We anal

同時發(fā)生

integrated

Lecture Notes in Computer Sciencehttp://image.papertrans.cn/a/image/152918.jpg

兒童

Kinetic

Arno Wolter,Michaela Grahl,J?rg Ehlerso specific judgment aggregation procedures to a whole class of such procedures, and we obtain stronger results by considering not only the classical complexity (NP-hardness) but the parameterized complexity (W[2]-hardness) of these problems with respect to natural parameters. Furthermore, we introdu