Sentence examples for maximizing expected gain from inspiring English sources

Given this model, we could then compare human performance to ideal performance maximizing expected gain.

We emphasize that the optimal solution maximizing expected gain is computed with each particular condition's mean total time, not with mean total time averaged across conditions.

We use the terms "gain" and "reward" interchangeably, and we used the terms "optimal" and "ideal" to describe behavior maximizing expected gain.

In considering any human performance it is natural to first ask how close performance comes to maximizing expected gain or expected utility.

Maximizing expected gain requires that we take into account the rewards and penalties associated with different movement outcomes.

We derive the optimal tradeoff that maximizes expected gain.

In contrast, we find that subjects do not allocate time between two movements so as to maximize expected gain.

This model allowed us to predict the allocations of time that maximized expected gain for each condition and to compare human performance to ideal.

There are several previous studies demonstrating that human subjects can adjust the duration of single movements so as to nearly maximize expected gain [3] [5].

We conclude that, while single movements may be planned optimally (or nearly so), as past research indicates, the movement planning system fails to maximize expected gain in planning sequences of as few as two movements, a limitation on movement planning that could be construed as a form of bounded rationality [28], [29].

Here, increasing the entropy over goal states corresponds to the concept of a novelty bonus (Kakade and Dayan 2002) or information gain, whereas maximizing expected utility corresponds to exploitation.