This paper analyzes two classes of consensus algorithms in presence of bounded measurement errors. The considered protocols adopt an updating rule based either on constant or vani...
In this paper, we develop a theoretical understanding of multi-sensory knowledge and user context and their interrelationships. This is used to develop a generic representation fr...
Whether or not a critical threshold exists when epidemic diseases are spread in complex networks is a problem attracting attention from researchers in several disciplines. In 2001...
PAC-MDP algorithms approach the exploration-exploitation problem of reinforcement learning agents in an effective way which guarantees that with high probability, the algorithm pe...
In this paper we propose a scaling-up method that is applicable to essentially any induction algorithm based on discrete search. The result of applying the method to an algorithm ...