Current crowdsourcing platforms provide little support for worker feedback. Workers are sometimes invited to post free text describing their experience and preferences in completing tasks. They can also use forums such as Turker Nation to exchange preferences on tasks and requesters. In fact, crowdsourcing platforms rely heavily on observing workers and inferring their preferences implicitly. I...

The main objective of this study is to examine how repeated choice affects preference learning in stated preference experiments. We test different hypotheses related to preference learning by analyzing response patterns and asking respondents in a choice experiment to report their experienced certainty when going through the choice tasks. In a split-sample test, we show that follow-up choice ce...

People’s choices can be predicted given information about their preferences. Learning people’s preferences is the inverse problem of inferring preferences from choices. Given the apparent relationship between choice prediction and preference learning, it is natural to ask whether the two are mutually consistent. Given weak assumptions, we show that no single, consistent model of the relationshi...

After an emergency event (EE) happens, emergency decision making (EDM) is a common and effective way to deal with the emergency situation, which plays an important role in mitigating its level of harm. In the real world, it is a big challenge for an individual emergency manager (EM) to make a proper and comprehensive decision for coping with an EE. Consequently, many practical EDM problems driv...

Consistency of preference relations is associated with the study of the transitivity property. This is clearly related to the scales used for associating preferences values to judgements, and the conditions used to represent transitivity. Both issues, the scale to use and the consistency property, have been studied in the multiplicative model as well as in the fuzzy one. However, we make note t...

In group decision making, users’ behaviour are influenced by their long-term and group-induced preferences. However, how to leverage them is challenging due to their dynamic nature, which is also dependent on the specific group settings. In our work, we employ a group recommendation model that utilizes both types of preferences and we analyze alternative ways of combing them, under diverse grou...

On the basis of previous work by various investigators (2, 3, 5, 6), the present study was designed to test the following hypotheses about firstborns: (a) They will score higher on the Edwards Personal Preference Schedule (EPPS) need for Affiliation scales (6), and need for Achievement scales (5) than other birth-order groups. (b) They will score higher on the College Entrance Exan1ination Boar...

Abstract. We study the optimal rates of convergence for estimating a prior distribution over a VC class from a sequence of independent data sets respectively labeled by independent target functions sampled from the prior. We specifically derive upper and lower bounds on the optimal rates under a smoothness condition on the correct prior, with the number of samples per data set equal the VC dime...

Multi-Attribute Reverse Auctions (MARAs) are excellent protocols to automate negotiation among sellers. Eliciting the buyer′s preferences and determining the winner are both challenging problems for MARAs. To solve these problems, we propose two algorithms namely MAUT* and CP-net*, which are respectively the improvement of the Multi-Attribute Utility Theory (MAUT) and constrained CP-net. The bu...