Abstract
Abstract : General additive functions called rewards are defined on a 'regular' finite-state Markov-renewal process. The asymptotic form of the mean total reward in (O, t) has previously been obtained, and it is known that the total rewards are joint-normally distributed as t approaches infinity. This paper finds the dominant asymptotic term in the covariance of the total rewards as a simple function of the moments of the per-transition rewards, and the 'bias' term of the mean total rewards. Special formulas for the dominant covariance term of 'number of visits', and 'occupation time' in given states are also derived.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
