Sentence examples for precision belief from inspiring English sources

Above, we introduced 3 perceptual models and 3 response models ("precision", "belief", and "surprise").

> -wrap-foot> Comparing the 3 response model families (i.e., the precision, belief and surprise models for each of the 3 versions of the perceptual model) showed that the response model based upon precision was clearly superior to the belief and the surprise model (Table  2).

Specifically, using a generic hierarchical Bayesian scheme (Mathys et al. 2011), we compared 3 alternative models of how subjects might update estimates of CV across trials (perceptual models) and crossed these with 3 alternative hypotheses about how posterior beliefs (precision, belief, and surprise) might inform decision making within trials (response models).

He notes that it is not the case that it is always unreasonable or impossible for you to have precise beliefs: in that case precision could serve as a regulative ideal.

In conclusion, our findings associate dopaminergic rich midbrain activity with the expected precision of beliefs about controlled outcomes, namely the confidence of reaching a desired goal.

Recently, we proposed a generic model based on active (Bayesian) inference wherein dopamine encodes the precision of beliefs about optimal policies.

In particular, the precision of beliefs about completing actions manifests in the efficiency of action selection, often conceived of in terms of winner take all mechanisms.

In the setting of choice behavior, this scheme implies that dopamine reports the expected certainty or precision of beliefs about policies and thereby the confidence a policy will deliver an outcome during purposeful and planned behavior.

It may not be straightforward to cast wanting or incentive salience in terms of formal (active) inference; however, the close relationship between the salience of incentivizing cues and the confidence or precision in beliefs that cued outcomes can or will be attained is self-evident.

On Monday, Gilles Simon took to the court at the Australian Open after a marathon in the previous round and could not muster the energy, the precision or the belief to avoid a mismatch in his fourth-round encounter with Andy Murray.

Some researchers have questioned the practicality of obtaining the numerical probabilities with sufficient precision to create belief networks for large-scale applications.