Sentence examples for model of intuitive from inspiring English sources

We have proposed a novel model of intuitive attribution that takes into account both backward- and forward-looking aspects of responsibility.

We review the main theoretical and empirical issues that arise from this literature and propose a novel model of intuitive judgments of responsibility.

The MEG analysis focused on the five conditions set up to test the plausibility of the proposed neural model of intuitive processing that is, the notion of the OFC functioning as an early integrator of incomplete stimulus information.

Building on this theoretical work, we will propose a novel model of intuitive judgments of responsibility that is a function of both pivotality (whether an agent made a difference to the outcome) and criticality (how important the agent is perceived to be for the outcome, before any actions are taken).

This article had two major aims: (a) to introduce the structural model approach as a framework for exploring attributions of causal responsibility; and (b) to present and empirically test a new model of intuitive judgments of responsibility that combines both pivotality and criticality.

The proposed preliminary neural model of intuitive coherence judgments, as suggested by Bar and colleagues (2006), conceives of the OFC as an integrator of incomplete stimulus input that signals a first coarse representation of the information forward to further processing areas.

One could hand-set parameters of the model to intuitive values; however, we expect that fitting the model will allow for sample-specific adjustments to inter-experimental technical variability and inter-sample variation from tumour normal admixture (so called tumour cellularity) in the tumour samples.

And for other reasons which we shall see, there is a good reason to accept the claim that the largest solutions are good mathematical models of the intuitive concepts.

Therefore, in this paper, we discuss the possibility of the computational modeling of an intuitive inference guided by emotion in which random-seeming neural excitation plays the role of a probability-based parallel search of values.

This enables a formal model-engineering methodology which combines the convenience of intuitive modeling in Timed Rebeca with formal verification in Real-Time Maude.

The B1G1 model holds a lot of intuitive appeal, which has likely contributed to its proliferation.