Miami University, Ohio
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A Probabilistic Solution Generator of Good Enough Designs for Simulation
We build a probabilistic solution generator using the learning automata theory, which can generate a small set of "good enough" designs with a predetermined high probability. The main goal of our work is to reduce a large design population to a much smaller subset of good designs that can be analyzed thoroughly in a subsequent simulation study to identify the best design among them. In the process of building the solution generator, a rough-cut design evaluation method with a high noise error is employed in order to screen designs very rapidly _ may it be an approximate method, a heuristic approach, or short simulation runs. The solution generator has been applied successfully to several serious test problems with noisy objectives
Evaluation of the Ohio double jeopardy demonstration project
The goal of Ohio s Double Jeopardy project was to support families in their efforts to plan for secure futures for family members with mental retardation/developmental disabilities (MR/DD) and for their aging parents. This report summarizes the results of the evaluation that was conducted to document the effectiveness of training offered as part of the Double Jeopardy project. Specifically, this report addresses the effectiveness of: a) legal and financial training for professionals; b) cross-training of professionals from the aging and MR/DD networks about the populations that are served and how the networks operate; c) training about life planning for professionals from both the aging and MR/DD networks; and d) training about life planning for family members