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 ...
Owing to the increase in both heterogeneity and complexity in today’s networking systems, the need arises for an architecture for network-based services that provides flexibilit...
Christos Chrysoulas, Evangelos Haleplidis, Robert ...
This paper examines, by argument, the dynamics of sequences of behavioural choices made, when non-cooperative restricted-memory agents learn in partially observable stochastic gam...
Regret minimization has proven to be a very powerful tool in both computational learning theory and online algorithms. Regret minimization algorithms can guarantee, for a single de...
The need for new theoretical and experimental approaches to understand dynamic and heterogeneous behavior in complex economic and social systems is increasing recently. An approac...