PURPOSE Very few studies examined the issue of regret on choosing colorectal cancer (CRC) screening tests. We evaluated the determinants of regret and tested the hypothesis that regret over screening choices was associated with poorer screening compliance. METHODS A bowel cancer screening centre invited all Hong Kong citizens aged 50-70 years who were asymptomatic of CRC to participate in fre...

Potential based no-regret dynamics are shown to be related to fictitious play. Roughly, these are ε-best reply dynamics where ε is the maximal regret, which vanishes with time. This allows for alternative and sometimes much shorter proofs of known results on convergence of no-regret dynamics to the set of Nash equilibria.

A model is considered where firms internalize the regret costs that consumers experience when they see an unexpected price change. Regret costs are assumed to be increasing in the size of price changes and this can explain why the size of price increases is less sensitive to inflation than in models with fixed costs of changing prices. The latter predict unrealistically large responses of price...

the non-definite multi-attribute decision making problem is the further expansion of research to the traditional multi-attribute decision making problem. In the actual decision-making, because of policy-making question's complexity, decision-making information acquisition costs and other reasons, the decision information which the policy-maker can obtain are mostly ambiguous, so in the real lif...

Recent research has emphasized the exponential increase in the online regret experience among online users. Such experience results in poor satisfaction, brand switching, and even service discontinuity. However, little prior research has investigated the relative influence of online platform characteristics and individual differences (such as demographics) in predicting the online regret experi...

No-regret algorithms are powerful tools for learning in online convex problems that have received increased attention in recent years. Considering affine and external regret, we investigate what happens when a set of no-regret learners (voters) merge their respective strategies in each learning iteration to a single, common one in form of a convex combination. We show that an agent who executes...

Recent work on follow the perturbed leader (FTPL) algorithms for the adversarial multi-armed bandit problem has highlighted the role of the hazard rate of the distribution generating the perturbations. Assuming that the hazard rate is bounded, it is possible to provide regret analyses for a variety of FTPL algorithms for the multi-armed bandit problem. This paper pushes the inquiry into regret ...

The current study aims to explore how the decision-making style of maximizing affects subjective well-being (SWB), which mainly focuses on the confirmation of the mediator role of regret and suppressing role of achievement motivation. A total of 402 Chinese undergraduate students participated in this study, in which they responded to the maximization, regret, and achievement motivation scales a...

Several theories have been proposed to account for variation in the intensity of life regrets. Variables hypothesized to affect the intensity of regret include: whether the regretted decision was an action or an inaction, the degree to which the decision was justified, and the life domain of the regret. No previous study has compared the effects of these key predictors in a single model in orde...

UCT, a state-of-the art algorithm for Monte Carlo tree sampling (MCTS), is based on UCB, a sampling policy for the Multi-armed Bandit Problem (MAB) that minimizes the accumulated regret. However, MCTS differs from MAB in that only the final choice, rather than all arm pulls, brings a reward, that is, the simple regret, as opposite to the cumulative regret, must be minimized. This ongoing work a...