Maintenance can be the factor of either increasing or decreasing system's availability, so it is valuable work to evaluate a maintenance policy from cost and availability point of view, simultaneously and according to decision maker's priorities. This study proposes a Partially Observable Markov Decision Process (POMDP) framework for a partially observable and stochastically deteriorating syste...

Related DatabasesWeb of Science You must be logged in with an active subscription to view this.Article DataHistorySubmitted: 20 April 2020Accepted: 03 February 2021Published online: 29 2021KeywordsMarkov decision process, partial observation, long-run average payoffAMS Subject Headings90C39, 90C40, 37A50, 60J20Publication DataISSN (print): 0363-0129ISSN (online): 1095-7138Publisher: Society for...

We seek to find the robust policy that maximizes the expected cumulative reward for the worst case when a partially observable Markov decision process (POMDP) has uncertain parameters whose values are only known to be in a given region. We prove that the robust value function, which represents the expected cumulative reward that can be obtained with the robust policy, is convex with respect to ...

The Partially Observable Markov Decision Process (POMDP) framework has proven useful in planning domains where agents must balance actions that provide knowledge and actions that provide reward. Unfortunately, most POMDPs are complex structures with a large number of parameters. In many real-world problems, both the structure and the parameters are difficult to specify from domain knowledge alo...

Predictive maintenance is based on observing an indicator of the state of a system, at different intervals of time which gives the decision maker some information about the exact state. The problem is to obtain an optimal replacement policy minimizing the long run expected cost per unit of time and to formulate it as a partially observable Markov decision process.

The process of understanding the meaning of a written passage inherently involves dynamic manipulation and composition of ideas. Starting from this observation this thesis proposes an artificial system for text understanding in which the semantic space containing the possible meanings of the analyzed text is selectively explored by a partially observable Markov decision process trained to effec...

In this paper, we propose a framework for conversational robots that facilitates fourparticipant groups. In three-participant conversations, the minimum unit for multiparty conversations, social imbalance, in which a participant is left behind in the current conversation, sometimes occurs. In such scenarios, a conversational robot has the potential to facilitate situations as the fourth partici...