Sentence examples for flexible reasoning from inspiring English sources

At the center of algebraic reasoning is relational thinking, which involves coordinating quantities in a mathematical expression, often without computation, using flexible reasoning about quantities and transforming mathematical expressions into equivalent ones.

The fuzzy system and fuzzy neural network models have the advantages of incorporating flexible reasoning as expert systems when compared to hybrid neural networks; however, they require the development of new prediction enhancement techniques for the improvement of their forecasts.

Empirical Bayes methods are designed to leverage aspects of both Bayesian and frequentist statistical inference by using the powerful and flexible reasoning tools of Bayesian statistics, but exploiting the massively parallel structure of the data to infer prior probability distributions in a frequentist-type setting.

To deal with the race's new challenges, Stanford has souped up its robot, called "Junior," with a new, more flexible system of reasoning, more capable of improvising and planning around unexpected contingencies.

The strengths of reduction-based systems are that they (i) directly scale with newer versions of solvers and (ii) can be easily adapted to specific needs, which is mirrored by a quite flexible support of reasoning problems and argumentation semantics.

However, a review of longitudinal birth cohort studies in the medical literature reveals that impairment of executive functions—high-order brain processes responsible for planning, flexible thinking, abstract reasoning, problem solving, and inhibition of inappropriate actions most consistently reflects prenatal PCB exposure [ EHP 117:7–16; Boucher et al.].

This combination of action-based reasoning with flexible localized search has yielded a powerful and efficient planning framework that is useful for challenging realistic domains.

Its advantages include: (1) providing direct probability statements which are what most people wrongly assume they are getting from conventional statistics; (2) formally incorporating previous information in statistical inference of a data set, a natural approach which we follow in everyday reasoning; and (3) flexible, adaptive research designs allowing multiple looks at accumulating study data.

Ontologies focus on a qualitative description of the biomedical domain and are commonly represented in formal languages which facilitate automated discovery of contradictory statements and flexible access to knowledge through automated reasoning.

It can be concluded that ANG is a simple yet flexible and effective classifier, and the evidential reasoning based parameter selection approach for ANG is also effective.

We first present the approach for a simple language and show how incremental reasoning can be combined with flexible code reuse.