The rational model proposes in fact an approach guided by well defined problems, clearly understandable preferences, describable and enumerable alternatives, ability to calculate the best choices, capable of maximizing the benefits and minimize costs.
In this case, we find the optimum choice for in terms of maximizing the average sum rate.
One answer to this, one that could come from within the Pure Choice paradigm, is to say that simply maximizing the number of available options is not necessarily the best way of maximizing meaningful choice, or of respecting autonomy (which is what matters more fundamentally).
As we have reported previously [42], the observed choice biases are nearly optimal in terms of maximizing reward collection across an experimental session.
We agree with this general approach, but feel that the choice is more appropriately analyzed in terms of maximizing survival than in minimizing energy expenditure.
DSM will be increasingly important in enabling a marriage between these various technologies and systems so as to enhance the utilization of the power system and enable increased reliability and enhanced consumer choice while maximizing the penetration of distributed energy resources including photovoltaics, energy storage and efficient buildings, appliances and devices.
For example, economists routinely write mathematical models of market economies that assume consumers and producers make choices to maximize their well-being.
The first fact is that there is an optimum choice of Q which maximizes the pre-constant value of the throughput.
In ML the choice of parameters that maximizes the data likelihood is obtained through a numerical optimization procedure.
Knowing that public policies of different sectors (e.g. transport, education, housing) can affect the health of the population, HIA aims to inform decision-makers in their choice of alternatives to maximize positive and mitigate negative health impacts or actively promote health [ 1- 3].
