Task completion plans normally resemble best-case scenarios and yield overly optimistic predictions of completion times. The authors induced participants to generate more pessimistic scenarios and examined completion predictions. Participants described a pessimistic scenario of task completion either alone or with an optimistic scenario. Pessimistic scenarios did not affect predictions or accur...

In original Data Envelopment Analysis (DEA) models for measuring the relative efficiencies of a set of Decision Making Units (DMUs) using various inputs to produce various outputs are limited to crisp data. To deal with imprecise data, the notion of fuzziness has been introduced. this paper develops a procedure to measure the efficiencies of DMUs with fuzzy observations. The basic idea is to tr...

The purpose of this paper is to develop an output oriented methodology for calculating productivity growth by using Malmquist productivity index (MPI) and two different data envelopment analysis (DEA) views (optimistic and pessimistic) simultaneously, and apply it to five Iranian Commercial Banks over the four time period (2009-2013). Consequently, we have proposed a new approach called the dou...

We study a variant of the pessimistic bilevel optimization problem, which comprises constraints that must be satisfied for any optimal solution of a subordinate (lower-level) optimization problem. We present conditions that guarantee the existence of optimal solutions in such a problem, and we characterize the computational complexity of various subclasses of the problem. We then focus on probl...

Uplift modeling is a machine learning technique that aims to model treatment effects heterogeneity. It has been used in business and health sectors to predict the effect of a specific action on a given individual. Despite its advantages, uplift models show high sensitivity to noise and disturbance, which leads to unreliable results. In this paper we show different approaches to address the prob...

In this paper, I consider the pessimistic induction construed as a deductive argument (specifically, reductio ad absurdum) and as an inductive argument (specifically, inductive generalization). I argue that both formulations of the pessimistic induction are fallacious. I also consider another possible interpretation of the pessimistic induction, namely, as pointing to counterexamples to the sci...