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Ranked decision systems -- recommenders, ad auctions, clinical triage queues -- must decide when to intervene in ranked outputs and when to abstain. We study when confidence-based abstention monotonically improves decision quality, and when…

Artificial Intelligence · Computer Science 2026-03-11 Ronald Doku

The consideration of nonstandard models of the real numbers and the definition of a qualitative ordering on those models provides a generalization of the principle of maximization of expected utility. It enables the decider to assign…

Computer Science and Game Theory · Computer Science 2007-05-23 Daniel Lehmann

When inferring the causal effect of one variable on another from correlational data, a common practice by professional researchers as well as lay decision makers is to control for some set of exogenous confounding variables. Choosing an…

Theoretical Economics · Economics 2023-05-31 Ran Spiegler

A structure called a decision making problem is considered. The set of outcomes (consequences) is partially ordered according to the decision maker's preferences. The problem is how these preferences affect a decision maker to prefer one of…

Category Theory · Mathematics 2007-05-23 Victor V. Rozen , Grigori Zhitomirski

Classical causal and statistical inference methods typically assume the observed data consists of independent realizations. However, in many applications this assumption is inappropriate due to a network of dependences between units in the…

Machine Learning · Computer Science 2019-07-02 Rohit Bhattacharya , Daniel Malinsky , Ilya Shpitser

Diffusion in a linear potential in the presence of position-dependent killing is used to mimic a default process. Different assumptions regarding transport coefficients, initial conditions, and elasticity of the killing measure lead to…

Computational Finance · Quantitative Finance 2015-05-30 Yuri A. Katz

Over the past two decades, considerable strides have been made in advancing neuroscientific techniques, yet challenges remain in attributing causality to observed associations. This review addresses a fundamental issue in observational…

Other Quantitative Biology · Quantitative Biology 2025-11-04 Eric W. Bridgeford , Brian S. Caffo , Maya B. Mathur , Russell A. Poldrack

In this paper, I develop and characterize two models of random attention that differ from each other with respect to the menu-dependence of the unobserved reference alternatives. In both models, the decision-maker pays attention to subsets…

Theoretical Economics · Economics 2025-12-23 Varun Bansal

This paper builds a rule for decisionmaking from the physical behavior of single neurons, the well established neural circuitry of mutual inhibition, and the evolutionary principle of natural selection. No axioms are used in the derivation…

Theoretical Economics · Economics 2023-02-21 Valdes Salvador , Gonzalo ValdesEdwards

We introduce a new formulation of the axiom of dependent choice that can be viewed as an abstract termination principle, which generalises the recursive path orderings used to establish termination of rewrite systems. We consider several…

Logic in Computer Science · Computer Science 2019-02-28 Thomas Powell

Outcome-dependent sampling designs are common in many different scientific fields including epidemiology, ecology, and economics. As with all observational studies, such designs often suffer from unmeasured confounding, which generally…

Methodology · Statistics 2020-10-13 Erin E. Gabriel , Michael C. Sachs , Arvid Sjölander

Most traditional models of uncertainty have focused on the associational relationship among variables as captured by conditional dependence. In order to successfully manage intelligent systems for decision making, however, we must be able…

Artificial Intelligence · Computer Science 2015-05-19 David Heckerman , Ross D. Shachter

In many areas of engineering and sciences, decision rules and control strategies are usually designed based on nominal values of relevant system parameters. To ensure that a control strategy or decision rule will work properly when the…

Probability · Mathematics 2020-06-16 Xinjia Chen

As we know, there is a controversy about the decision making under risk between economists and psychologists. We discuss to build a unified theory of risky choice, which would explain both of compensatory and non-compensatory theories. For…

Economics · Quantitative Finance 2017-03-24 Lamb Wubin , Naixin Ren

We study situations where a group of voters need to take a collective decision over a number of public issues, with the goal of getting a result that reflects the voters' opinions in a proportional manner. Our focus is on interconnected…

Computer Science and Game Theory · Computer Science 2025-09-25 Julian Chingoma , Umberto Grandi , Arianna Novaro

People are often reluctant to sell a house, or shares of stock, below the price at which they originally bought it. While this is generally not consistent with rational utility maximization, it does reflect two strong empirical regularities…

Computer Science and Game Theory · Computer Science 2021-06-02 Jon Kleinberg , Robert Kleinberg , Sigal Oren

During the last twenty years or so a wide range of realizability interpretations of classical analysis have been developed. In many cases, these are achieved by extending the base interpreting system of primitive recursive functionals with…

Logic in Computer Science · Computer Science 2015-03-13 Thomas Powell

For obtaining causal inferences that are objective, and therefore have the best chance of revealing scientific truths, carefully designed and executed randomized experiments are generally considered to be the gold standard. Observational…

Applications · Statistics 2008-11-12 Donald B. Rubin

When does society eventually learn the truth, or take the correct action, via observational learning? In a general model of sequential learning over social networks, we identify a simple condition for learning dubbed excludability.…

Theoretical Economics · Economics 2024-04-05 Navin Kartik , SangMok Lee , Tianhao Liu , Daniel Rappoport

We consider adaptive decision-making problems where an agent optimizes a cumulative performance objective by repeatedly choosing among a finite set of options. Compared to the classical prediction-with-expert-advice set-up, we consider…

Machine Learning · Computer Science 2023-04-10 Michael Muehlebach