We propose Markov random fields (MRFs) as a probabilistic mathematical model for unifying approaches to multi-robot coordination or, more specifically, distributed action selectio...
Jesse Butterfield, Odest Chadwicke Jenkins, Brian ...
Several multiagent reinforcement learning (MARL) algorithms have been proposed to optimize agents' decisions. Only a subset of these MARL algorithms both do not require agent...
ion for Stochastic Systems by Erlang's Method of Stages Joost-Pieter Katoen1 , Daniel Klink1 , Martin Leucker2 , and Verena Wolf3 1 RWTH Aachen University 2 TU Munich 3 EPF La...
Joost-Pieter Katoen, Daniel Klink, Martin Leucker,...
We consider the problem of estimating the model count (number of solutions) of Boolean formulas, and present two techniques that compute estimates of these counts, as well as eith...
In this work we analyze the complexity of local broadcasting in the physical interference model. We present two distributed randomized algorithms: one that assumes that each node ...
Olga Goussevskaia, Thomas Moscibroda, Roger Watten...