نتایج جستجو برای: feedback preferences

تعداد نتایج: 215290  

Journal: :International Journal of Information Technology and Decision Making 2012
J. M. Tapia García M. J. del Moral M. A. Martínez Enrique Herrera-Viedma

Interval fuzzy preference relations can be useful to express decision makers' preferences in group decision-making problems. Usually, we apply a selection process and a consensus process to solve a group decision situation. In this paper, we present a consensus model for group decisionmaking problems with interval fuzzy preference relations. This model is based on two consensus criteria, a cons...

Journal: :International Journal of Game Theory 2021

The paper presents a model of two-speed evolution in which the payoffs population game (or, alternatively, individual preferences) slowly adjust to changes aggregate behavior population. investigates how, for myopic agents with homogeneous preferences, environment caused by current may affect future and hence alter behavior. interaction between is based on symmetric two-strategy positive extern...

Journal: :SAGE Open 2023

Written corrective feedback (WCF) in enhancing writing proficiency has been the subject of numerous studies, but few studies have examined students’ perceptions about value on their written errors. Language teachers use global tools and techniques to give students work. How is delivered received by valued differently. The current study concentrated how interpret which WCF tactics they favor cla...

Journal: :International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 2010
Zhengping Wu Hao Wu

In e-commerce applications, the magnitude of products and the diversity of venders cause confusion and difficulty for the common consumer to choose the right product from a trustworthy vender. Although people have recognized the importance of feedback and reputation for the trustworthiness of individual venders and products, they still have difficulty when they have to make a shopping decision ...

Journal: :The International Journal of Robotics Research 2021

Reward functions are a common way to specify the objective of robot. As designing reward can be extremely challenging, more promising approach is directly learn from human teachers. Importantly, data teachers collected either passively or actively in variety forms: passive sources include demonstrations (e.g., kinesthetic guidance), whereas preferences comparative rankings) elicited. Prior rese...

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