A Preorder Relation for Markov Reward Processes

Asymptotic Behavior of Multivariate Reward Processes with Nonlinear Reward Functions

COVARIANCE MATRIX OF MULTIVARIATE REWARD PROCESSES WITH NONLINEAR REWARD FUNCTIONS

Multivariate reward processes with reward functions of constant rates, defined on a semi-Markov process, first were studied by Masuda and Sumita, 1991. Reward processes with nonlinear reward functions were introduced in Soltani, 1996. In this work we study a multivariate process , , where are reward processes with nonlinear reward functions respectively. The Laplace transform of the covar...

Real-Reward Testing for Probabilistic Processes (Extended Abstract)

We introduce a notion of real-valued reward testing for probabilistic processes by extending the traditional nonnegative-reward testing with negative rewards. In this richer testing framework, the may and must preorders turn out to be inverses. We show that for convergent processes with finitely many states and transitions, but not in the presence of divergence, the real-reward must-testing pre...

Real-reward testing for probabilistic processes

We introduce a notion of real-valued reward testing for probabilistic processes by extending the traditional nonnegative-reward testing with negative rewards. In this richer testing framework, the may and must preorders turn out to be inverses. We show that for convergent processes with finitely many states and transitions, but not in the presence of divergence, the real-reward must-testing pre...

Perceptive Evaluation for the Optimal Discounted Reward in Markov Decision Processes

We formulate a fuzzy perceptive model for Markov decision processes with discounted payoff in which the perception for transition probabilities is described by fuzzy sets. Our aim is to evaluate the optimal expected reward, which is called a fuzzy perceptive value, based on the perceptive analysis. It is characterized and calculated by a certain fuzzy relation. A machine maintenance problem is ...