Decentralized partially observable Markov decision process (DEC-POMDP) is an approach to model multi-robot decision making problems under uncertainty. Since it is NEXP-complete the...
A distributed constraint satisfaction problem (Distributed CSP) is a CSP in which variables and constraints are distributed among multiple automated agents, and various application...
Typically, Markov decision problems (MDPs) assume a single action is executed per decision epoch, but in the real world one may frequently execute certain actions in parallel. Thi...
—The research efforts of the DECIDE Research Group have resulted in a decision tool capable of handling imprecise information in complex decision situations. Some of the research...
Abstract. We consider the Steiner tree problem under a 2-stage stochastic model with recourse and finitely many scenarios (SSTP). Thereby, edges are purchased in the first stage wh...