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The contributions of these two learning rules to trial-by-trial preference adjustments are distinguishable when learning multistep decision tasks, and the hallmarks of both rules have been reported in both human (Daw, Gershman, Seymour, Dayan, & Dolan, 2011) and rodent (Akam, Dayan, & Costa, 2013; Miller, Erlich, Kopec, Botvinick, & Brody, 2014) behavior.
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Due to the accumulation and variation of preference, in the recommendation model we conduct an adaptive method including long-term and short-term preference adjustment to enhance the result of recommendation.
Reeves and Bordetski (1995) found that DMs are not always able to accurately express their preferences, and in order to make group preference stable and accurate, several rounds of preference adjustment is essential, to synthesize the views and information of the different DMs.
In our proposed model, the decision-making process with several rounds of discussions is introduced into the AHP, to develop a dynamic decision-making method that considers group interaction, which is characterized by the utilization of each round of preference information, as well as continuous preference adjustment.
Because TMT was found to vary by sex and TMTL was found to relate to hand preference, adjustment was made for these factors in all analyses.
In the older age groups (over about 75 years), the time preference adjustment has a minimal effect.
As TTO values are affected by time preferences, adjustment of observed TTO values can be considered.
Targeting at the abovementioned problems, the adaptive preference order adjustment method in coalition game is employed to assign the optimal fog communities for each user, namely the user transferring [27], by which the interest difference within each fog community can be minimized and a temporarily stable status of a given fog community can be achieved.
Concerned that the economy continues to exceed what the Fed considers to be its speed limit, the central bank put aside its recent preference for small adjustments to monetary policy in favor of an attention-grabbing increase of half a percentage point.
A sub set of patients will be asked to express a preference for the adjusted dentures at the end of the second adjustment period.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com