Stochastic orders can be applied to Markov reward models and used to aggregate models, while introducing a bounded error. Aggregation reduces the number of states in a model, miti...
Abstract--Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scan...
Markov chains are widely used in the context of performance and reliability evaluation of systems of various nature. Model checking of such chains with respect to a given (branchin...
Holger Hermanns, Joost-Pieter Katoen, Joachim Meye...
Abstract. This paper presents a model-checking approach for analyzing discrete-time Markov reward models. For this purpose, the temporal logic probabilistic CTL is extended with re...
—This paper proposes a novel method of learning a users preferred reward modalities for human-robot interaction through solving a cooperative training task. A learning algorithm ...