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The main goal of this paper is to describe an axiomatic utility theory for Dempster-Shafer belief function lotteries. The axiomatic framework used is analogous to von Neumann-Morgenstern's utility theory for probabilistic lotteries as…

Artificial Intelligence · Computer Science 2020-07-16 Thierry Denoeux , Prakash P. Shenoy

In "Recognizing the Maximum of a Sequence", Gilbert and Mosteller analyze a full information game where n measurements from an uniform distribution are drawn and a player (knowing n) must decide at each draw whether or not to choose that…

Probability · Mathematics 2018-05-30 Marcos Costa Santos Carreira

Kleinberg introduced three natural clustering properties, or axioms, and showed they cannot be simultaneously satisfied by any clustering algorithm. We present a new clustering property, Monotonic Consistency, which avoids the well-known…

Machine Learning · Computer Science 2022-04-05 Fabio Strazzeri , Rubén J. Sánchez-García

This paper managed to induce probability theory (sigma system) and possibility theory (max system) respectively from the clearly-defined randomness and fuzziness, while focusing the question why the key axiom of "maxitivity" is adopted for…

Artificial Intelligence · Computer Science 2025-01-03 Wei Mei , Ming Li , Yuanzeng Cheng , Limin Liu

In several decision-making problems, alternatives should be ranked on the basis of paired comparisons between them. We present an axiomatic approach for the universal ranking problem with arbitrary preference intensities, incomplete and…

Computer Science and Game Theory · Computer Science 2019-04-10 László Csató

Most social choice rules assume access to full rankings, while current alignment practice -- despite aiming for diversity -- typically treats voters as anonymous and comparisons as independent, effectively extracting only about one bit per…

Computer Science and Game Theory · Computer Science 2026-03-23 Luise Ge , Daniel Halpern , Gregory Kehne , Yevgeniy Vorobeychik

We defend a new theory of statistical evidence, which we call Robust Bayesianism (RB). We prove that, under widely accepted assumptions, RB entails the law of likelihood [Royall, 1997], the likelihood principle [Berger and Wolpert, 1988],…

Statistics Theory · Mathematics 2022-10-18 Conor Mayo-Wilson , Aditya Saraf

We study organizational elections in which each group nominates one candidate and receives as payoff its members expected utility under a probabilistic winning rule. We empirically justify a standard monotonicity assumption by simulating…

Computer Science and Game Theory · Computer Science 2026-02-06 Chuang-Chieh Lin , Chi-Jen Lu , Po-An Chen , Chih-Chieh Hung

We consider a stochastic matching model with a general compatibility graph, as introduced in \cite{MaiMoy16}. We prove that most common matching policies (including FCFM, priorities and random) satisfy a particular sub-additive property,…

Probability · Mathematics 2023-05-09 Pascal Moyal , Ana Busic , Jean Mairesse

A central issue in ecology today is that of the factors determining the relative abundance of species within a natural community. The proper application of the principles of statistical physics to the problem of species abundance…

Populations and Evolution · Quantitative Biology 2011-05-10 Michael G. Bowler , Colleen K. Kelly

Coherent sets of desirable gamble sets is used as a model for representing an agents opinions and choice preferences under uncertainty. In this paper we provide some results about the axioms required for coherence and the natural extension…

Artificial Intelligence · Computer Science 2024-05-17 Catrin Campbell-Moore

Mathematical theory of selection systems is developed for a wide class of dynamical models of inhomogeneous populations with discrete time. The Price equation and its particular case, the Fisher Fundamental theorem of natural selection…

Populations and Evolution · Quantitative Biology 2007-05-23 Georgy P. Karev

The theory of combinatorial game (like board games) and the theory of social games (where one looks for Nash equilibria) are normally considered as two separate theories. Here we shall see what comes out of combining the ideas. The central…

Probability · Mathematics 2010-05-28 Peter Harremoes

The Gibbard-Satterthwaite theorem states that every non-dictatorial election rule among at least three alternatives can be strategically manipulated. We prove a quantitative version of the Gibbard-Satterthwaite theorem: a random…

Combinatorics · Mathematics 2011-05-26 Ehud Friedgut , Gil Kalai , Nathan Keller , Noam Nisan

Game-theoretic probability uses the structure of gambles to define a concept like probability, but which is more flexible and robust. We show that results in game-theoretic probability can be thought of as minimax theorems for specific…

Probability · Mathematics 2025-12-25 Rafael Frongillo

We introduce the notion of a reproducible algorithm in the context of learning. A reproducible learning algorithm is resilient to variations in its samples -- with high probability, it returns the exact same output when run on two samples…

Machine Learning · Computer Science 2023-04-17 Russell Impagliazzo , Rex Lei , Toniann Pitassi , Jessica Sorrell

This paper shows the existence of independent random matching of a large (continuum) population in both static and dynamic systems, which has been popular in the economics and genetics literatures. We construct a joint agent-probability…

Probability · Mathematics 2007-05-23 Darrell Duffie , Yeneng Sun

Social networks are increasingly being used to conduct polls. We introduce a simple model of such social polling. We suppose agents vote sequentially, but the order in which agents choose to vote is not necessarily fixed. We also suppose…

Computer Science and Game Theory · Computer Science 2013-02-08 Serge Gaspers , Victor Naroditskiy , Nina Narodytska , Toby Walsh

Maximum entropy principle identifies forces conjugated to observables and the thermodynamic relations between them, independent upon their underlying mechanistic details. For data about state distributions or transition statistics, the…

Statistical Mechanics · Physics 2023-12-08 Ying-Jen Yang , Hong Qian

We introduce a "high probability" framework for repeated games with incomplete information. In our non-equilibrium setting, players aim to guarantee a certain payoff with high probability, rather than in expected value. We provide a high…

Computer Science and Game Theory · Computer Science 2015-09-30 Payam Delgosha , Amin Gohari , Mohammad Akbarpour