Consider a finite data set where each observation consists of a bundle of contingent consumption chosen by an agent from a constraint set of such bundles. We develop a general procedure for testing the consistency of this data set with a broad class of models of choice under risk and under...

Consider a finite data set where each observation consists of a bundle of contingent consumption chosen by an agent from a constraint set of such bundles. We develop a general procedure for testing the consistency of this data set with a broad class of models of choice under risk and under...

We establish a class of fully nonlinear conditional expectations. Similarly to the usage of linear expectations when a probabilistic description of uncertainty is present, we observe analogue quantitative and qualitative properties. The type of nonlinearity captures the agents sentiments of...

We develop a nonparametric procedure, called the lattice method, for testing the consistency of contingent consumption data with a broad class of models of choice under risk and under uncertainty. Our method allows for risk loving and elation seeking behavior and can be used to calculate, via...

The alpha-maxmin model is a prominent example of preferences under Knightian uncertainty as it allows to distinguish ambiguity and ambiguity attitude. These preferences are dynamically inconsistent for nontrivial versions of α. In this paper, we derive a recursive, dynamically consistent...

The literature on proper scoring rules has mostly studied the case of risk neutral agents. We analytically investigate how risk averse, expected utility maximizing forecasters behave when presented with risk neutral proper scoring rules. If the state variable is binary, risk averse agents shade...

Nash is famous for many inventions, but it is less known that he, simultaneously with Marschak, also was the first to axiomatize expected utility for risk. In particular, these authors were the first to state the independence condition, a condition that should have been but was not stated by von...

We define and discuss Savage games, which are ordinal games of incomplete information set in L. J. Savage's framework of purely subjective uncertainty. Every Bayesian game is ordinally equivalent to a Savage game. However, Savage games are free of priors, probabilities and payoffs. Players'...

We report some experiments conducted to test whether ambiguity influences behavior in a coordination game. We study the behavior of subjects in the presence of ambiguity and attempt to determine whether they prefer to choose an ambiguity safe option. We find that this strategy, which is not...

Artificial Intelligence (AI) scientists are challenged to create intelligent, autonomous agents that can make rational decisions. In this challenge, they confront two questions: what decision theory to follow and how to implement it in AI systems. This paper provides answers to these questions...