Bayesian learning in undirected graphical models--computing posterior distributions over parameters and predictive quantities-is exceptionally difficult. We conjecture that for ge...
—The subject of this work is the patrolling of an environment with the aid of a team of autonomous agents. We consider both the design of open-loop trajectories with optimal prop...
Fabio Pasqualetti, Antonio Franchi, Francesco Bull...
This paper introduces the even-odd POMDP, an approximation to POMDPs in which the world is assumed to be fully observable every other time step. The even-odd POMDP can be converte...
In this chapter we present recent contributions in the field of sequential job scheduling on network machines which work in parallel; these are subject to temporary unavailability...
Florian Diedrich, Klaus Jansen, Ulrich M. Schwarz,...
Graphs are powerful data structures that have many attractive properties for object representation. However, some basic operations are difficult to define and implement, for ins...
Miquel Ferrer, Ernest Valveny, Francesc Serratosa,...