e p urpose of this paper is to propose a solution methodology for a missile defense problem involving the sequential allocation of defensive r esources over a series of engagements. The problem is cast as a dynamic programming/Markovian decision problem, which is computationally intractable by exact methods because of its large number o f s tates and its complex modeling issues. We h a ve employed a Neuro-Dynamic Programming (NDP) framework, whereby t he cost-to-go function is approximated using neural network architectures that are trained on simulated data. We report on the performance obtained using several different t raining methods, and we compare this performance with the optimal. Keywords| T h e ater Missile Defense, Dynamic Programming, Neuro-Dynamic Programming, Reinforcement L e a rning.

Eccentric viewing training is successful in improving the reading ability of individuals with a central scotoma. This paper shows evidence of the success of training provided by the voluntary sector and funded by adult literacy funding. The results are comparable with those reported in the literature.

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This retrospective study of US versus WGL in BCS demonstrated no significant difference in the positive margin rate, although a trend was observed in favor of the WGL group. We have provided further evidence for the debate on the accuracy of US and WGL for non-palpable breast lesions. Available data remains sparse, and our results contradict the findings of other comparative studies.

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