Self-optimizing Cutting Process Using Learning Process Models

Models for optimizing the learning process.

This paper is concerned with showing how certain instructional problems can be reformulated as problems in the mathematical theory of optimization. A common instructional paradigm is outlined and a notational system is proposed which allows the paradigm to be restated as a multistage decision process with an explicit mathematical learning model embedded within it. The notion of an optimal stimu...

Using Process Data for Finding Self-optimizing Controlled Variables

In the process industry it is often not known how well a process is operated, and without a good model it is difficult to tell if operation can be further improved. We present a data-based method for finding a combination of measurements which can be used for obtaining an estimate of how well the process is operated, and which can be used in feedback as a controlled variable. To find the variab...

Reinforcement Learning using Optimistic Process Filtered Models

An important problem in reinforcement learning is determining how to act while learning sometimes referred to as the exploration-exploitation dilemma or the problem of optimal learning. The problem is intractable, usually solved through approximation such as by being optimistic in the face of uncertainty. In environments with inherent determinism, arising for example from known process template...

Models for Optimizing the Learn ~ Ng Process

Optimizing Red Blood Cells Consumption Using Markov Decision Process

In healthcare systems, one of the important actions is related to perishable products such as red blood cells (RBCs) units that its consumption management in different periods can contribute greatly to the optimality of the system. In this paper, main goal is to enhance the ability of medical community to organize the RBCs units’ consumption in way to deliver the unit order timely with a focus ...