Reinforcement learning problems are commonly tackled with temporal difference methods, which attempt to estimate the agent's optimal value function. In most real-world proble...
Most adaptive delivery mechanisms for streaming multimedia content do not explicitly consider user-perceived quality when making adaptation decisions. We show that an optimal adap...
This paper addresses the formal verification of diagnosis systems. We tackle the problem of diagnosability: given a partially observable dynamic system, and a diagnosis system obs...
Alessandro Cimatti, Charles Pecheur, Roberto Cavad...
Constraint networks have been shown to be useful in formulating such diverse problems as scene labeling, natural language parsing, and temporal reasoning. Given a constraint netwo...
Abstract. We propose a dynamic process for network evolution, aiming at explaining the emergence of the small world phenomenon, i.e., the statistical observation that any pair of i...
Augustin Chaintreau, Pierre Fraigniaud, Emmanuelle...