— Multi-agent coordination problems can be cast as distributed optimization tasks. Probability Collectives (PCs) are techniques that deal with such problems in discrete and conti...
We describe how to take a set of interaction traces produced by different pairs of players in a two-player repeated game, and combine them into a composite strategy. We provide an...
The application of Reinforcement Learning (RL) algorithms to learn tasks for robots is often limited by the large dimension of the state space, which may make prohibitive its appli...
Andrea Bonarini, Alessandro Lazaric, Marcello Rest...
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 ...
In this paper we introduce a finite automaton called partial finite automaton to recognize partial languages. We have defined three classes of partial languages, viz., local pa...