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We study binary opinion dynamics in a fully connected network of interacting agents. The agents are assumed to interact according to one of the following rules: (1) Voter rule: An updating agent simply copies the opinion of another randomly…

Probability · Mathematics 2022-03-04 Arpan Mukhopadhyay , Ravi R. Mazumdar , Rahul Roy

We consider a simple sequential allocation procedure for sharing indivisible items between agents in which agents take turns to pick items. Supposing additive utilities and independence between the agents, we show that the expected utility…

Artificial Intelligence · Computer Science 2013-04-24 Thomas Kalinowski , Nina Nardoytska , Toby Walsh

In peer selection agents must choose a subset of themselves for an award or a prize. As agents are self-interested, we want to design algorithms that are impartial, so that an individual agent cannot affect their own chance of being…

Computer Science and Game Theory · Computer Science 2020-05-01 Nicholas Mattei , Paolo Turrini , Stanislav Zhydkov

The problem of combining p-values is an old and fundamental one, and the classic assumption of independence is often violated or unverifiable in many applications. There are many well-known rules that can combine a set of arbitrarily…

Statistics Theory · Mathematics 2025-03-21 Matteo Gasparin , Ruodu Wang , Aaditya Ramdas

We consider how an agent should update her uncertainty when it is represented by a set $\P$ of probability distributions and the agent observes that a random variable $X$ takes on value $x$, given that the agent makes decisions using the…

Artificial Intelligence · Computer Science 2007-11-27 Peter D. Grunwald , Joseph Y. Halpern

We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about conditional…

Artificial Intelligence · Computer Science 2013-02-21 Peter L. Spirtes , Christopher Meek , Thomas S. Richardson

Estimating the dependences between random variables, and ranking them accordingly, is a prevalent problem in machine learning. Pursuing frequentist and information-theoretic approaches, we first show that the p-value and the mutual…

Machine Learning · Computer Science 2012-07-02 Harald Steck

We study the self-assembly of a complex network of collaborations among self-interested agents. The agents can maintain different levels of cooperation with different partners. Further, they continuously, selectively, and independently…

Physics and Society · Physics 2015-05-13 Anne-Ly Do , Lars Rudolf , Thilo Gross

We investigate the mechanism design problem faced by a principal who hires \emph{multiple} agents to gather and report costly information. Then, the principal exploits the information to make an informed decision. We model this problem as a…

Computer Science and Game Theory · Computer Science 2023-07-13 Federico Cacciamani , Matteo Castiglioni , Nicola Gatti

The choice of sample size in the context of co-primary endpoints for a randomised trial is discussed. Current guidance can leave endpoints with unequal marginal power. A method is provided to achieve equal marginal power by using the…

Methodology · Statistics 2026-02-23 Simon Bond

We consider a multi-agent optimal resource sharing problem that is represented by a linear program. The amount of resource to be shared is fixed, and agents belong to a population that is characterized probabilistically so as to allow…

Optimization and Control · Mathematics 2021-09-29 Alessandro Falsone , Kostas Margellos , Jacopo Zizzo , Maria Prandini , Simone Garatti

A collection of $n$ random events is said to be $(n - 1)$-wise independent if any $n - 1$ events among them are mutually independent. We characterise all probability measures with respect to which $n$ random events are $(n - 1)$-wise…

Probability · Mathematics 2022-11-04 Karthik Natarajan , Arjun Kodagehalli Ramachandra , Colin Tan

Most work in algorithmic fairness to date has focused on discrete outcomes, such as deciding whether to grant someone a loan or not. In these classification settings, group fairness criteria such as independence, separation and sufficiency…

Machine Learning · Computer Science 2020-02-18 Daniel Steinberg , Alistair Reid , Simon O'Callaghan , Finnian Lattimore , Lachlan McCalman , Tiberio Caetano

We study a setting where a set of agents engage in pairwise exchanges of freely replicable goods (e.g., digital goods such as data), where two agents grant each other a copy of a good they possess in exchange for a good they lack. Such…

Computer Science and Game Theory · Computer Science 2026-03-16 Shangyuan Yang , Kirthevasan Kandasamy

Classical results in voting theory show that strategic manipulation by voters is inevitable if a voting rule simultaneously satisfy certain desirable properties. Motivated by this, we study the relevant question of how often a voting rule…

Computer Science and Game Theory · Computer Science 2015-02-17 Palash Dey , Y. Narahari

We consider the design of experiments to evaluate treatments that are administered by self-interested agents, each seeking to achieve the highest evaluation and win the experiment. For example, in an advertising experiment, a company wishes…

Methodology · Statistics 2015-09-18 Panos Toulis , David C. Parkes , Elery Pfeffer , James Zou

The sequential allocation protocol is a simple and popular mechanism to allocate indivisible goods, in which the agents take turns to pick the items according to a predefined sequence. While this protocol is not strategy-proof, it has been…

Computer Science and Game Theory · Computer Science 2019-11-27 Michele Flammini , Hugo Gilbert

We study a version of the minority game in which one agent is allowed to join the game in a random fashion. It is shown that in the crowded regime, i.e., for small values of the memory size $m$ of the agents in the population, the agent…

Statistical Mechanics · Physics 2009-11-10 K. F. Yip , T. S. Lo , P. M. Hui , N. F. Johnson

It is well known that conditional independence can be used to factorize a joint probability into a multiplication of conditional probabilities. This paper proposes a constructive definition of inter-causal independence, which can be used to…

Artificial Intelligence · Computer Science 2013-02-28 Nevin Lianwen Zhang , David L Poole

We study the problem of decision-making in the setting of a scarcity of shared resources when the preferences of agents are unknown a priori and must be learned from data. Taking the two-sided matching market as a running example, we focus…

Computer Science and Game Theory · Computer Science 2021-11-24 Xiaowu Dai , Michael I. Jordan
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