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In this paper, we consider the model that the information on the rewards in vector-valued Markov decision processes includes imprecision or ambiguity. The fuzzy reward model is analyzed as follows: The fuzzy reward is represented by the fuzzy set on the multi-dimensional Euclidian space R p and the infinite horizon fuzzy expected discounted reward(FEDR)(More)
BACKGROUND The purpose of this study was to reveal the clinical characteristics of nonleukemic granulocytic sarcoma (GS) and an association between the therapeutic regimens and the nonleukemic period. METHOD Clinical records of 2 patients reported here and 72 patients gathered using a literature search on Medline from other institutions were analyzed. The(More)
PURPOSE The purpose of this study is to examine the role of Iodine-123-labeled 15-(p-iodophenyl)-3R,S-methylpentadecanoic acid (BMIPP) scintigraphy in patients with cardiac sarcoidosis. METHODS AND MATERIALS Study materials were six patients with pathologically proven cardiac sarcoidosis. BMIPP and resting Thallium-201 (201Tl) myocardial scintigraphy,(More)
We consider utility-constrained Markov decision processes. The expected utility of the total discounted reward is maximized subject to multiple expected utility constraints. By introducing a corresponding Lagrange function, a saddle-point theorem of the utility constrained optimization is derived. The existence of a constrained optimal policy is(More)
In this paper, a Markov decision model with uncertain transition matrices, which allow a matrix to fluctuate at each step in time, is described by the use of fuzzy sets. We find a pareto optimal policy maximizing the infinite horizon fuzzy expected discounted reward over all stationary policies under some partial order. The pareto optimal policies are(More)
The effectiveness of the automated motion correction software (INSTILL, Philips Medical Systems Co. Ltd., Andover, USA) proposed by Matsumoto et al. to prevent motion artifact in quantitative gated SPECT, was tested with a technetium-99m point source and cardiac phantom. INSTILL well corrected the error due to point source movement during acquisition up to(More)
In this paper, the average cases of Markov decision processes with uncertainty is considered. That is, a controlled Markov set-chain model with a finite state and action space is developed by an interval arithmetic analysis, and we will find a Pareto optimal policy which maximizes the average expected rewards over all stationary policies under a new partial(More)