We develop a novel mechanism for coordinated, distributed multiagent planning. We consider problems stated as a collection of single-agent planning problems coupled by common soft...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...
We consider a multiagent resource allocation domain where the marginal production of each resource is diminishing. A set of identical, self-interested agents requires access to sh...
The application of reinforcement learning algorithms to Partially Observable Stochastic Games (POSG) is challenging since each agent does not have access to the whole state inform...
Alessandro Lazaric, Mario Quaresimale, Marcello Re...
In this paper, we describe two mission critical applications currently deployed by Telecom Italia in the Operations Support System domains. The first one called "Network Neut...