It is often suggested that when opinions differ among individuals in a group, the should be aggregated to form compromise. This paper compares two approaches aggregating opinions, linear pooling and what I call opinion agglomeration. In evaluating both strategies, propose pragmatic criterion, No Regrets, entailing an aggregation strategy prevent groups from buying selling bets on events at pric...

We revisit the celebrated Bayesian persuasion setting and examine how well Sender can perform when ignorant of Receiver's utility. Taking an adversarial approach, we measure signaling scheme performance via (additive) regret over a single instance. focus on Receiver with two actions: adoption rejection , assuming that aims to persuade adopt. show while Sender's total ignorance utility is extrem...

In many areas of Artificial Intelligence (AI), we are interested in helping people make better decisions. This help can result in two advantages. First, computers can process large amounts of data and perform quick calculations, leading to better decisions. Second, if a user does not have to think about some decisions, they have more time to focus on other things they find important. Since user...

The unfavorable comparison between the obtained and expected outcomes of our choices may elicit disappointment. When the comparison is made with the outcome of alternative actions, emotions like regret can serve as a learning signal. Previous work showed that both anticipated disappointment and regret influence decisions. In addition, experienced regret is associated with higher emotional respo...

What is the legal significance of regret following a reproductive decision or outcome? In Gonzales v. Carhart, a Supreme Court majority offered one answer to this question, famously invoking the regret of some women for their past abortions as a reason to uphold a federal law criminalizing a particular abortion procedure. But Gonzales is not the first case to confront what I call “reproduction ...

This paper investigates, for the first time in the literature, the approximation of min-max (regret) versions of classical problems like shortest path, minimum spanning tree, and knapsack. For a bounded number of scenarios, we establish fully polynomial-time approximation schemes for the min-max versions of these problems, using relationships between multi-objective and min-max optimization. Us...

In a partial monitoring game, the learner repeatedly chooses an action, the environment responds with an outcome, and then the learner suffers a loss and receives a feedback signal, both of which are fixed functions of the action and the outcome. The goal of the learner is to minimize his regret, which is the difference between his total cumulative loss and the total loss of the best fixed acti...